Anton Schwaighofer

Principal Research Engineer

出版物

表示方法:

- Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting
  
  Harshita Sharma, Maxwell C. Reynolds, Valentina Salvatelli, Anne-Marie G. Sykes, Kelly K. Horst, Anton Schwaighofer, Maximilian Ilse, Olesya Melnichenko, Sam Bond-Taylor, Fernando Pérez-García, Vamshi K. Mugu, Alex Chan, Ceylan Colak, Shelby A. Swartz, Motassem Nashawaty, Austin J. Gonzalez, Heather A. Ouellette, B. S. Erdal, Beth A. Schueler, Maria T. Wetscherek, Noel Codella, Mohit Jain, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Stephanie Hyland, Panos Korfiatis, Ashish Khandelwal, Javier Alvarez-Valle
  
  November 2025
  
  Preprint プロジェクト
- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, 巻32(2): pp. 1-61
  
  Publication DOI プロジェクト
- Insights into a radiology-specialised multimodal large language model with sparse autoencoders
  
  Kenza Bouzid, Shruthi Bannur, Felix Meissen, Daniel Coelho de Castro, Anton Schwaighofer, Javier Alvarez-Valle, Stephanie Hyland
  
  Actionable Interpretability Workshop - ICML 2025 | July 2025
  
  DOI Publication Publication プロジェクト
- Exploring Scalable Medical Image Encoders Beyond Text Supervision
  
  Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Machine Intelligence | January 2025, 巻7: pp. 119-130
  
  Publication DOI Access Access プロジェクト
- MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models
  
  Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle
  
  Machine Learning for Health Symposium 2024 | December 2024
  
  Publication Preprint プロジェクト
- MAIRA-2: Grounded Radiology Report Generation
  
  Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland
  
  MSR-TR-2024-18 | June 2024
  
  Microsoft による投稿
  
  Preprint PDF Github Access プロジェクト
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
  Preprint Publication プロジェクト
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, 巻15
  
  DOI Publication PDF
- MAIRA-1: A specialised large multimodal model for radiology report generation
  
  Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle
  
  MSR-TR-2023-47 | November 2023
  
  Microsoft による投稿
  
  Publication プロジェクト
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication プロジェクト
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access プロジェクト
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
  Preprint 動画 Access Access プロジェクト
- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, 巻13(1161): pp. 1-11
  
  Publication Github プロジェクトプロジェクト
- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
  PDF Preprint プロジェクトプロジェクトプロジェクトプロジェクト
- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
  Publication 動画 Github プロジェクト
- Budget Optimization for Sponsored Search:Censored Learning in MDPs
  
  Kareem Amin, Michael Kearns, Peter Key, Anton Schwaighofer
  
  Uncertainty in Artificial Intelligence (UAI) | August 2012
  
  公開日
- Scalable Clustering and Keyword Suggestion for Online Advertisements
  
  Anton Schwaighofer, Joaquin Quiñonero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich
  
  Proceedings of ADKDD 2009: 3rd Annual International Workshop on Data Mining and Audience Intelligence for Advertising | January 2009
  
  公開日
- Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
  
  Anton Schwaighofer
  
  Journal of Chemical Information and Modelling | January 2007, 巻47(2): pp. 407-424
  
  公開日公開日
- Estimating the Domain of Applicability for Machine Learning QSAR RModels: A Study on Aqueous Solubility of Drug Discovery Molecules
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  Journal of Computer Aided Molecular Design | January 2007
  
  公開日
- Gaussian Processes in Practice
  
  Neil D. Lawrence, Anton Schwaighofer, Joaquin Quiñonero Candela
  
  January 2007
  
  (Editors)
  
  公開日
- Machine Learning Models for Lipophilicity and their Domain of Applicability
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  Molecular Pharmaceutics | January 2007, 巻4: pp. 524-538
  
  公開日
- Predicting Lipophilicity of Drug Discovery Molecules using Gaussian Process Models
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  ChemMedChem | January 2007, 巻2: pp. 1265-1267
  
  公開日
- Structure Learning with Nonparametric Decomposable Models
  
  Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter
  
  Artificial Neural Networks - ICANN 2007 | January 2007
  
  公開日
- Learning Gaussian Process Kernels via Hierarchical Bayes
  
  Anton Schwaighofer, Volker Tresp, Kai Yu
  
  Advances in Neural Information Processing Systems 17 | January 2005
  
  Advances in Neural Information Processing Systems 17
  
  公開日
- Learning Gaussian Processes from Multiple Tasks
  
  Kai Yu, Volker Tresp, Anton Schwaighofer
  
  Machine Learning: Proceedings of the 22nd International Conference (ICML 2005) | January 2005
  
  公開日
- GPPS: A Gaussian Process Positioning System for Cellular Networks
  
  Anton Schwaighofer, Marian Grigoraş, Volker Tresp, Clemens Hoffmann
  
  Advances in Neural Information Processing Systems 16 | January 2004
  
  公開日
- Mining Functional Modules in Genetic Networks with Decomposable Graphical Models
  
  Mathäus Dejori, Anton Schwaighofer, Volker Tresp, Martin Stetter
  
  OMICS A Journal of Integrative Biology | January 2004, 巻8: pp. 176-188
  
  公開日
- Probabilistic Memory Based Collaborative Filtering: Learning Individual and Social Preferences
  
  Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-Peter Kriegel
  
  IEEE Transactions on Knowledge and Data Engineering | January 2004, 巻16: pp. 56-69
  
  公開日
- Classification of Rheumatoid Joint Inflammation Based on Laser Imaging
  
  Anton Schwaighofer, Volker Tresp, Peter Mayer, Andreas Krause, Jürgen Beuthan, Helmut Rost, Gerhard Metzger, Gerhard A. Müller, Alexander K. Scheel
  
  IEEE Transactions on Biomedical Engineering | January 2003, 巻50: pp. 375-382
  
  公開日
- Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
  
  Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang, Hong-Jiang Zhang
  
  Uncertainty in Artificial Intelligence: Proceedings of the 19th Conference (UAI-2003) | January 2003
  
  公開日
- The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging
  
  Anton Schwaighofer, Volker Tresp, Peter Mayer, Alexander K. Scheel, Gerhard A. Müller
  
  Advances in Neural Information Processing Systems 15 | January 2003
  
  Advances in Neural Information Processing Systems 15
  
  公開日
- Transductive and Inductive Methods for Approximate Gaussian Process Regression
  
  Anton Schwaighofer, Volker Tresp
  
  Advances in Neural Information Processing Systems 15 | January 2003
  
  公開日

- Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting
  
  Harshita Sharma, Maxwell C. Reynolds, Valentina Salvatelli, Anne-Marie G. Sykes, Kelly K. Horst, Anton Schwaighofer, Maximilian Ilse, Olesya Melnichenko, Sam Bond-Taylor, Fernando Pérez-García, Vamshi K. Mugu, Alex Chan, Ceylan Colak, Shelby A. Swartz, Motassem Nashawaty, Austin J. Gonzalez, Heather A. Ouellette, B. S. Erdal, Beth A. Schueler, Maria T. Wetscherek, Noel Codella, Mohit Jain, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Stephanie Hyland, Panos Korfiatis, Ashish Khandelwal, Javier Alvarez-Valle
  
  November 2025
  
  Preprint プロジェクト
- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, 巻32(2): pp. 1-61
  
  Publication DOI プロジェクト
- Insights into a radiology-specialised multimodal large language model with sparse autoencoders
  
  Kenza Bouzid, Shruthi Bannur, Felix Meissen, Daniel Coelho de Castro, Anton Schwaighofer, Javier Alvarez-Valle, Stephanie Hyland
  
  Actionable Interpretability Workshop - ICML 2025 | July 2025
  
  DOI Publication Publication プロジェクト
- Exploring Scalable Medical Image Encoders Beyond Text Supervision
  
  Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Machine Intelligence | January 2025, 巻7: pp. 119-130
  
  Publication DOI Access Access プロジェクト
- MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models
  
  Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle
  
  Machine Learning for Health Symposium 2024 | December 2024
  
  Publication Preprint プロジェクト
- MAIRA-2: Grounded Radiology Report Generation
  
  Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland
  
  MSR-TR-2024-18 | June 2024
  
  Microsoft による投稿
  
  Preprint PDF Github Access プロジェクト
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
  Preprint Publication プロジェクト
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, 巻15
  
  DOI Publication PDF
- MAIRA-1: A specialised large multimodal model for radiology report generation
  
  Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle
  
  MSR-TR-2023-47 | November 2023
  
  Microsoft による投稿
  
  Publication プロジェクト
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication プロジェクト
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access プロジェクト
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
  Preprint 動画 Access Access プロジェクト
- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, 巻13(1161): pp. 1-11
  
  Publication Github プロジェクトプロジェクト
- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
  PDF Preprint プロジェクトプロジェクトプロジェクトプロジェクト
- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
  Publication 動画 Github プロジェクト
- Budget Optimization for Sponsored Search:Censored Learning in MDPs
  
  Kareem Amin, Michael Kearns, Peter Key, Anton Schwaighofer
  
  Uncertainty in Artificial Intelligence (UAI) | August 2012
  
  公開日
- Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
  
  Anton Schwaighofer
  
  Journal of Chemical Information and Modelling | January 2007, 巻47(2): pp. 407-424
  
  公開日公開日
- Estimating the Domain of Applicability for Machine Learning QSAR RModels: A Study on Aqueous Solubility of Drug Discovery Molecules
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  Journal of Computer Aided Molecular Design | January 2007
  
  公開日
- Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting
  
  Harshita Sharma, Maxwell C. Reynolds, Valentina Salvatelli, Anne-Marie G. Sykes, Kelly K. Horst, Anton Schwaighofer, Maximilian Ilse, Olesya Melnichenko, Sam Bond-Taylor, Fernando Pérez-García, Vamshi K. Mugu, Alex Chan, Ceylan Colak, Shelby A. Swartz, Motassem Nashawaty, Austin J. Gonzalez, Heather A. Ouellette, B. S. Erdal, Beth A. Schueler, Maria T. Wetscherek, Noel Codella, Mohit Jain, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Stephanie Hyland, Panos Korfiatis, Ashish Khandelwal, Javier Alvarez-Valle
  
  November 2025
  
  Preprint プロジェクト
- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, 巻32(2): pp. 1-61
  
  Publication DOI プロジェクト
- Insights into a radiology-specialised multimodal large language model with sparse autoencoders
  
  Kenza Bouzid, Shruthi Bannur, Felix Meissen, Daniel Coelho de Castro, Anton Schwaighofer, Javier Alvarez-Valle, Stephanie Hyland
  
  Actionable Interpretability Workshop - ICML 2025 | July 2025
  
  DOI Publication Publication プロジェクト
- Exploring Scalable Medical Image Encoders Beyond Text Supervision
  
  Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Machine Intelligence | January 2025, 巻7: pp. 119-130
  
  Publication DOI Access Access プロジェクト
- MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models
  
  Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle
  
  Machine Learning for Health Symposium 2024 | December 2024
  
  Publication Preprint プロジェクト
- MAIRA-2: Grounded Radiology Report Generation
  
  Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland
  
  MSR-TR-2024-18 | June 2024
  
  Microsoft による投稿
  
  Preprint PDF Github Access プロジェクト
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, 巻15
  
  DOI Publication PDF
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication プロジェクト
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access プロジェクト
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
  Preprint 動画 Access Access プロジェクト
- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, 巻13(1161): pp. 1-11
  
  Publication Github プロジェクトプロジェクト
- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
  PDF Preprint プロジェクトプロジェクトプロジェクトプロジェクト
- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
  Publication 動画 Github プロジェクト
- Machine Learning Models for Lipophilicity and their Domain of Applicability
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  Molecular Pharmaceutics | January 2007, 巻4: pp. 524-538
  
  公開日
- Predicting Lipophilicity of Drug Discovery Molecules using Gaussian Process Models
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  ChemMedChem | January 2007, 巻2: pp. 1265-1267
  
  公開日
- Classification of Rheumatoid Joint Inflammation Based on Laser Imaging
  
  Anton Schwaighofer, Volker Tresp, Peter Mayer, Andreas Krause, Jürgen Beuthan, Helmut Rost, Gerhard Metzger, Gerhard A. Müller, Alexander K. Scheel
  
  IEEE Transactions on Biomedical Engineering | January 2003, 巻50: pp. 375-382
  
  公開日
- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, 巻32(2): pp. 1-61
  
  Publication DOI プロジェクト
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
  Preprint Publication プロジェクト
- Exploring Scalable Medical Image Encoders Beyond Text Supervision
  
  Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Machine Intelligence | January 2025, 巻7: pp. 119-130
  
  Publication DOI Access Access プロジェクト
- MAIRA-1: A specialised large multimodal model for radiology report generation
  
  Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle
  
  MSR-TR-2023-47 | November 2023
  
  Microsoft による投稿
  
  Publication プロジェクト
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access プロジェクト
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
  Preprint 動画 Access Access プロジェクト
- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, 巻13(1161): pp. 1-11
  
  Publication Github プロジェクトプロジェクト
- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
  PDF Preprint プロジェクトプロジェクトプロジェクトプロジェクト
- Budget Optimization for Sponsored Search:Censored Learning in MDPs
  
  Kareem Amin, Michael Kearns, Peter Key, Anton Schwaighofer
  
  Uncertainty in Artificial Intelligence (UAI) | August 2012
  
  公開日
- Scalable Clustering and Keyword Suggestion for Online Advertisements
  
  Anton Schwaighofer, Joaquin Quiñonero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich
  
  Proceedings of ADKDD 2009: 3rd Annual International Workshop on Data Mining and Audience Intelligence for Advertising | January 2009
  
  公開日
- Structure Learning with Nonparametric Decomposable Models
  
  Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter
  
  Artificial Neural Networks - ICANN 2007 | January 2007
  
  公開日
- Gaussian Processes in Practice
  
  Neil D. Lawrence, Anton Schwaighofer, Joaquin Quiñonero Candela
  
  January 2007
  
  (Editors)
  
  公開日
- Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
  
  Anton Schwaighofer
  
  Journal of Chemical Information and Modelling | January 2007, 巻47(2): pp. 407-424
  
  公開日公開日
- Learning Gaussian Process Kernels via Hierarchical Bayes
  
  Anton Schwaighofer, Volker Tresp, Kai Yu
  
  Advances in Neural Information Processing Systems 17 | January 2005
  
  Advances in Neural Information Processing Systems 17
  
  公開日
- Learning Gaussian Processes from Multiple Tasks
  
  Kai Yu, Volker Tresp, Anton Schwaighofer
  
  Machine Learning: Proceedings of the 22nd International Conference (ICML 2005) | January 2005
  
  公開日
- Probabilistic Memory Based Collaborative Filtering: Learning Individual and Social Preferences
  
  Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-Peter Kriegel
  
  IEEE Transactions on Knowledge and Data Engineering | January 2004, 巻16: pp. 56-69
  
  公開日
- Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
  
  Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang, Hong-Jiang Zhang
  
  Uncertainty in Artificial Intelligence: Proceedings of the 19th Conference (UAI-2003) | January 2003
  
  公開日
- GPPS: A Gaussian Process Positioning System for Cellular Networks
  
  Anton Schwaighofer, Marian Grigoraş, Volker Tresp, Clemens Hoffmann
  
  Advances in Neural Information Processing Systems 16 | January 2004
  
  公開日
- Mining Functional Modules in Genetic Networks with Decomposable Graphical Models
  
  Mathäus Dejori, Anton Schwaighofer, Volker Tresp, Martin Stetter
  
  OMICS A Journal of Integrative Biology | January 2004, 巻8: pp. 176-188
  
  公開日
- Transductive and Inductive Methods for Approximate Gaussian Process Regression
  
  Anton Schwaighofer, Volker Tresp
  
  Advances in Neural Information Processing Systems 15 | January 2003
  
  公開日
- The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging
  
  Anton Schwaighofer, Volker Tresp, Peter Mayer, Alexander K. Scheel, Gerhard A. Müller
  
  Advances in Neural Information Processing Systems 15 | January 2003
  
  Advances in Neural Information Processing Systems 15
  
  公開日

- Insights into a radiology-specialised multimodal large language model with sparse autoencoders
  
  Kenza Bouzid, Shruthi Bannur, Felix Meissen, Daniel Coelho de Castro, Anton Schwaighofer, Javier Alvarez-Valle, Stephanie Hyland
  
  Actionable Interpretability Workshop - ICML 2025 | July 2025
  
  DOI Publication Publication プロジェクト
- MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models
  
  Harshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel Coelho de Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson (nee Murfet), Maria Teodora Wetscherek, Stephanie Hyland, Javier Alvarez-Valle
  
  Machine Learning for Health Symposium 2024 | December 2024
  
  Publication Preprint プロジェクト
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
  Preprint Publication プロジェクト
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication プロジェクト
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access プロジェクト
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
  Preprint 動画 Access Access プロジェクト
- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
  PDF Preprint プロジェクトプロジェクトプロジェクトプロジェクト
- Budget Optimization for Sponsored Search:Censored Learning in MDPs
  
  Kareem Amin, Michael Kearns, Peter Key, Anton Schwaighofer
  
  Uncertainty in Artificial Intelligence (UAI) | August 2012
  
  公開日
- Scalable Clustering and Keyword Suggestion for Online Advertisements
  
  Anton Schwaighofer, Joaquin Quiñonero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich
  
  Proceedings of ADKDD 2009: 3rd Annual International Workshop on Data Mining and Audience Intelligence for Advertising | January 2009
  
  公開日
- Structure Learning with Nonparametric Decomposable Models
  
  Anton Schwaighofer, Mathäus Dejori, Volker Tresp, Martin Stetter
  
  Artificial Neural Networks - ICANN 2007 | January 2007
  
  公開日
- Gaussian Processes in Practice
  
  Neil D. Lawrence, Anton Schwaighofer, Joaquin Quiñonero Candela
  
  January 2007
  
  (Editors)
  
  公開日
- Learning Gaussian Process Kernels via Hierarchical Bayes
  
  Anton Schwaighofer, Volker Tresp, Kai Yu
  
  Advances in Neural Information Processing Systems 17 | January 2005
  
  Advances in Neural Information Processing Systems 17
  
  公開日
- Learning Gaussian Processes from Multiple Tasks
  
  Kai Yu, Volker Tresp, Anton Schwaighofer
  
  Machine Learning: Proceedings of the 22nd International Conference (ICML 2005) | January 2005
  
  公開日
- GPPS: A Gaussian Process Positioning System for Cellular Networks
  
  Anton Schwaighofer, Marian Grigoraş, Volker Tresp, Clemens Hoffmann
  
  Advances in Neural Information Processing Systems 16 | January 2004
  
  公開日
- Transductive and Inductive Methods for Approximate Gaussian Process Regression
  
  Anton Schwaighofer, Volker Tresp
  
  Advances in Neural Information Processing Systems 15 | January 2003
  
  公開日
- The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging
  
  Anton Schwaighofer, Volker Tresp, Peter Mayer, Alexander K. Scheel, Gerhard A. Müller
  
  Advances in Neural Information Processing Systems 15 | January 2003
  
  Advances in Neural Information Processing Systems 15
  
  公開日
- Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
  
  Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang, Hong-Jiang Zhang
  
  Uncertainty in Artificial Intelligence: Proceedings of the 19th Conference (UAI-2003) | January 2003
  
  公開日
- Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting
  
  Harshita Sharma, Maxwell C. Reynolds, Valentina Salvatelli, Anne-Marie G. Sykes, Kelly K. Horst, Anton Schwaighofer, Maximilian Ilse, Olesya Melnichenko, Sam Bond-Taylor, Fernando Pérez-García, Vamshi K. Mugu, Alex Chan, Ceylan Colak, Shelby A. Swartz, Motassem Nashawaty, Austin J. Gonzalez, Heather A. Ouellette, B. S. Erdal, Beth A. Schueler, Maria T. Wetscherek, Noel Codella, Mohit Jain, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Stephanie Hyland, Panos Korfiatis, Ashish Khandelwal, Javier Alvarez-Valle
  
  November 2025
  
  Preprint プロジェクト
- MAIRA-2: Grounded Radiology Report Generation
  
  Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Anton Schwaighofer, Sam Bond-Taylor, Maximilian Ilse, Fernando Pérez-García, Valentina Salvatelli, Harshita Sharma, Felix Meissen, Mercy Ranjit, Shaury Srivastav, Julia Gong, Fabian Falck, Ozan Oktay, Anja Thieme, Matthew P Lungren, Maria Teodora Wetscherek, Javier Alvarez-Valle, Stephanie Hyland
  
  MSR-TR-2024-18 | June 2024
  
  Microsoft による投稿
  
  Preprint PDF Github Access プロジェクト
- MAIRA-1: A specialised large multimodal model for radiology report generation
  
  Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Mercy Ranjit, Anton Schwaighofer, Fernando Pérez-García, Valentina Salvatelli, Shaury Srivastav, Anja Thieme, Noel Codella, Matthew P Lungren, Maria Teodora Wetscherek, Ozan Oktay, Javier Alvarez-Valle
  
  MSR-TR-2023-47 | November 2023
  
  Microsoft による投稿
  
  Publication プロジェクト
- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, 巻32(2): pp. 1-61
  
  Publication DOI プロジェクト
- Exploring Scalable Medical Image Encoders Beyond Text Supervision
  
  Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Matthew P Lungren, Noel Codella, Stephanie Hyland, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Machine Intelligence | January 2025, 巻7: pp. 119-130
  
  Publication DOI Access Access プロジェクト
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, 巻15
  
  DOI Publication PDF
- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, 巻13(1161): pp. 1-11
  
  Publication Github プロジェクトプロジェクト
- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
  Publication 動画 Github プロジェクト
- Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
  
  Anton Schwaighofer
  
  Journal of Chemical Information and Modelling | January 2007, 巻47(2): pp. 407-424
  
  公開日公開日
- Machine Learning Models for Lipophilicity and their Domain of Applicability
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  Molecular Pharmaceutics | January 2007, 巻4: pp. 524-538
  
  公開日
- Estimating the Domain of Applicability for Machine Learning QSAR RModels: A Study on Aqueous Solubility of Drug Discovery Molecules
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  Journal of Computer Aided Molecular Design | January 2007
  
  公開日
- Predicting Lipophilicity of Drug Discovery Molecules using Gaussian Process Models
  
  Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller
  
  ChemMedChem | January 2007, 巻2: pp. 1265-1267
  
  公開日
- Probabilistic Memory Based Collaborative Filtering: Learning Individual and Social Preferences
  
  Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-Peter Kriegel
  
  IEEE Transactions on Knowledge and Data Engineering | January 2004, 巻16: pp. 56-69
  
  公開日
- Mining Functional Modules in Genetic Networks with Decomposable Graphical Models
  
  Mathäus Dejori, Anton Schwaighofer, Volker Tresp, Martin Stetter
  
  OMICS A Journal of Integrative Biology | January 2004, 巻8: pp. 176-188
  
  公開日
- Classification of Rheumatoid Joint Inflammation Based on Laser Imaging
  
  Anton Schwaighofer, Volker Tresp, Peter Mayer, Andreas Krause, Jürgen Beuthan, Helmut Rost, Gerhard Metzger, Gerhard A. Müller, Alexander K. Scheel
  
  IEEE Transactions on Biomedical Engineering | January 2003, 巻50: pp. 375-382
  
  公開日

Anton Schwaighofer

出版物

Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Insights into a radiology-specialised multimodal large language model with sparse autoencoders

Exploring Scalable Medical Image Encoders Beyond Text Supervision

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

MAIRA-2: Grounded Radiology Report Generation

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

MAIRA-1: A specialised large multimodal model for radiology report generation

Exploring the Boundaries of GPT-4 in Radiology

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Active label cleaning for improved dataset quality under resource constraints

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Budget Optimization for Sponsored Search:Censored Learning in MDPs

Scalable Clustering and Keyword Suggestion for Online Advertisements

Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach

Estimating the Domain of Applicability for Machine Learning QSAR RModels: A Study on Aqueous Solubility of Drug Discovery Molecules

Gaussian Processes in Practice

Machine Learning Models for Lipophilicity and their Domain of Applicability

Predicting Lipophilicity of Drug Discovery Molecules using Gaussian Process Models

Structure Learning with Nonparametric Decomposable Models

Learning Gaussian Process Kernels via Hierarchical Bayes

Learning Gaussian Processes from Multiple Tasks

GPPS: A Gaussian Process Positioning System for Cellular Networks

Mining Functional Modules in Genetic Networks with Decomposable Graphical Models

Probabilistic Memory Based Collaborative Filtering: Learning Individual and Social Preferences

Classification of Rheumatoid Joint Inflammation Based on Laser Imaging

Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes

The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging

Transductive and Inductive Methods for Approximate Gaussian Process Regression

Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Insights into a radiology-specialised multimodal large language model with sparse autoencoders

Exploring Scalable Medical Image Encoders Beyond Text Supervision

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

MAIRA-2: Grounded Radiology Report Generation

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

MAIRA-1: A specialised large multimodal model for radiology report generation

Exploring the Boundaries of GPT-4 in Radiology

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Active label cleaning for improved dataset quality under resource constraints

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Budget Optimization for Sponsored Search:Censored Learning in MDPs

Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach

Estimating the Domain of Applicability for Machine Learning QSAR RModels: A Study on Aqueous Solubility of Drug Discovery Molecules

Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Insights into a radiology-specialised multimodal large language model with sparse autoencoders

Exploring Scalable Medical Image Encoders Beyond Text Supervision

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

MAIRA-2: Grounded Radiology Report Generation

Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

Exploring the Boundaries of GPT-4 in Radiology

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Active label cleaning for improved dataset quality under resource constraints

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Machine Learning Models for Lipophilicity and their Domain of Applicability

Predicting Lipophilicity of Drug Discovery Molecules using Gaussian Process Models

Classification of Rheumatoid Joint Inflammation Based on Laser Imaging

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Exploring Scalable Medical Image Encoders Beyond Text Supervision

MAIRA-1: A specialised large multimodal model for radiology report generation

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Active label cleaning for improved dataset quality under resource constraints

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Budget Optimization for Sponsored Search:Censored Learning in MDPs

Scalable Clustering and Keyword Suggestion for Online Advertisements

Structure Learning with Nonparametric Decomposable Models

Gaussian Processes in Practice