A Generative Model of Words and Relationships from Multiple Sources. - Stephanie L. Hyland; Theofanis Karaletsos; Gunnar Rätsch (AAAI, 2016)

Neural Document Embeddings for Intensive Care Patient Mortality Prediction. - Paulina Grnarova; Florian Schmidt 005; Stephanie L. Hyland; Carsten Eickhoff (CoRR, 2016)

Knowledge Transfer with Medical Language Embeddings. - Stephanie L. Hyland; Theofanis Karaletsos; Gunnar Rätsch (CoRR, 2016)

Learning Unitary Operators with Help From u(n). - Stephanie L. Hyland; Gunnar Rätsch (AAAI, 2017)

Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs. - Cristóbal Esteban; Stephanie L. Hyland; Gunnar Rätsch (CoRR, 2017)

A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients. - Stephanie L. Hyland; Martin Faltys; Matthias Hüser; Xinrui Lyu; Cristóbal Esteban; Gunnar Rätsch; Tobias Merz (AMIA, 2018)

Predicting circulatory system deterioration in intensive care unit patients. - Stephanie L. Hyland; Matthias Hüser; Xinrui Lyu; Martin Faltys; Tobias Merz; Gunnar Rätsch (AIH@IJCAI, 2018)

Improving Clinical Predictions through Unsupervised Time Series Representation Learning. - Xinrui Lyu; Matthias Hüser; Stephanie L. Hyland; George Zerveas; Gunnar Rätsch (CoRR, 2018)

Machine learning for early prediction of circulatory failure in the intensive care unit. - Stephanie L. Hyland; Martin Faltys; Matthias Hüser; Xinrui Lyu; Thomas Gumbsch; Cristóbal Esteban; Christian Bock; Max Horn; Michael Moor; Bastian Rieck; Marc Zimmermann; Dean A. Bodenham; et al. (CoRR, 2019)

Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies. - Stefan G. Stark; Stephanie L. Hyland; Melanie Fernandes Pradier; Kjong-Van Lehmann; Andreas Wicki; Fernando Pérez-Cruz; Julia E. Vogt; Gunnar Rätsch (CoRR, 2019)

On the Intrinsic Privacy of Stochastic Gradient Descent. - Stephanie L. Hyland; Shruti Tople (CoRR, 2019)

Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. - Suproteem K. Sarkar; Subhrajit Roy; Emily Alsentzer; Matthew B. A. McDermott; Fabian Falck; Ioana Bica; Griffin Adams; Stephen Pfohl; Stephanie L. Hyland (ML4H@NeurIPS, 2020)

Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks. - Emma Rocheteau; Pietro Liò; Stephanie L. Hyland (CoRR, 2020)

ML4H Abstract Track 2020. - Emily Alsentzer; Matthew B. A. McDermott; Fabian Falck; Suproteem K. Sarkar; Subhrajit Roy; Stephanie L. Hyland (CoRR, 2020)

Inconsistencies in handling missing data across stages of prediction modelling: a review of methods used. - Antonia Tsvetanova; Glen P. Martin; Matthew Sperrin; Niels Peek; Iain E. Buchan; Stephanie L. Hyland (AMIA, 2021)

Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit. - Emma Rocheteau; Pietro Liò; Stephanie L. Hyland (CHIL, 2021)

Early prediction of respiratory failure in the intensive care unit. - Matthias Hüser; Martin Faltys; Xinrui Lyu; Chris Barber; Stephanie L. Hyland; Tobias M. Merz; Gunnar Rätsch (CoRR, 2021)

Predicting the impact of treatments over time with uncertainty aware neural differential equations. - Edward De Brouwer; Javier Gonzalez; Stephanie L. Hyland (AISTATS, 2022)

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. - Benedikt Boecking; Naoto Usuyama; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Stephanie L. Hyland; Maria Wetscherek; Tristan Naumann; Aditya V. Nori; Javier Alvarez-Valle; Hoifung Poon; Ozan Oktay (ECCV (36), 2022)

Predicting the impact of treatments over time with uncertainty aware neural differential equations. - Edward De Brouwer; Javier González Hernández; Stephanie L. Hyland (CoRR, 2022)

Looking for Out-of-Distribution Environments in Critical Care: A case study with the eICU Database. - Dimitris Spathis; Stephanie L. Hyland (CoRR, 2022)

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. - Shruthi Bannur; Stephanie L. Hyland; Qianchu Liu; Fernando Pérez-García; Maximilian Ilse; Daniel C. Castro; Benedikt Boecking; Harshita Sharma; Kenza Bouzid; Anja Thieme; Anton Schwaighofer; Maria Wetscherek; et al. (CVPR, 2023)

Exploring the Boundaries of GPT-4 in Radiology. - Qianchu Liu; Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Maria Wetscherek; Robert Tinn; Harshita Sharma; Fernando Pérez-García; Anton Schwaighofer; Pranav Rajpurkar; Sameer Tajdin Khanna; et al. (EMNLP, 2023)

Compatibility in Missing Data Handling Across the Prediction Model Pipeline: A Simulation Study. - Antonia Tsvetanova; Matthew Sperrin; David A. Jenkins; Niels Peek; Iain E. Buchan; Stephanie L. Hyland; Glen P. Martin (MedInfo, 2023)

MAIRA-1: A specialised large multimodal model for radiology report generation. - Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Mercy Ranjit; Anton Schwaighofer; Fernando Pérez-García; Valentina Salvatelli; Shaury Srivastav; Anja Thieme; Noel Codella; Matthew P. Lungren; et al. (CoRR, 2023)

Compositional Zero-Shot Domain Transfer with Text-to-Text Models. - Fangyu Liu 001; Qianchu Liu; Shruthi Bannur; Fernando Pérez-García; Naoto Usuyama; Sheng Zhang 012; Tristan Naumann; Aditya V. Nori; Hoifung Poon; Javier Alvarez-Valle; Ozan Oktay; Stephanie L. Hyland (Trans. Assoc. Comput. Linguistics, 2023)

Framing Machine Learning Opportunities for Hypotension Prediction in Perioperative Care: A Socio-technical Perspective: Socio-technical perspectives on hypotension prediction. - Pratik Ghosh; Karen L. Posner; Stephanie L. Hyland; Wil van Cleve; Melissa Bristow; Dustin R. Long; Konstantina Palla; Bala Nair; Christine Fong; Ronald Pauldine; Monica S. Vavilala; Kenton O'Hara (ACM Trans. Comput. Hum. Interact., 2023)

MAIRA at RRG24: A specialised large multimodal model for radiology report generation. - Shaury Srivastav; Mercy Ranjit; Fernando Pérez-García; Kenza Bouzid; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Harshita Sharma; Maximilian Ilse; Valentina Salvatelli; Sam Bond-Taylor; Fabian Falck; et al. (BioNLP@ACL, 2024)

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. - Nur Yildirim; Hannah Richardson; Maria Teodora Wetscherek; Junaid Bajwa; Joseph Jacob; Mark Ames Pinnock; Stephen Harris; Daniel Coelho de Castro; Shruthi Bannur; Stephanie L. Hyland; Pratik Ghosh; Mercy Ranjit; et al. (CHI, 2024)

MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models. - Harshita Sharma; Valentina Salvatelli; Shaury Srivastav; Kenza Bouzid; Shruthi Bannur; Daniel C. Castro; Maximilian Ilse; Sam Bond-Taylor; Mercy Prasanna Ranjit; Fabian Falck; Fernando Pérez-García; Anton Schwaighofer; et al. (ML4H@NeurIPS, 2024)

RAD-DINO: 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 C. Castro; Anton Schwaighofer; Matthew P. Lungren; Maria Wetscherek; Noel Codella; et al. (CoRR, 2024)

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; Fernando Pérez-García; et al. (CoRR, 2024)

MAIRA-2: Grounded Radiology Report Generation. - Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Anton Schwaighofer; Sam Bond-Taylor; Maximilian Ilse; Fernando Pérez-García; Valentina Salvatelli; Harshita Sharma; Felix Meissen; Mercy Ranjit; Shaury Srivastav; et al. (CoRR, 2024)

An X-Ray Is Worth 15 Features: Sparse Autoencoders for Interpretable Radiology Report Generation. - Ahmed Abdulaal; Hugo Fry; Nina Montaña Brown; Ayodeji Ijishakin; Jack Gao; Stephanie L. Hyland; Daniel C. Alexander; Daniel C. Castro (CoRR, 2024)

MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging. - Noel C. F. Codella; Ying Jin; Shrey Jain; Yu Gu; Ho Hin Lee; Asma Ben Abacha; Alberto Santamaría-Pang; Will Guyman; Naiteek Sangani; Sheng Zhang; Hoifung Poon; Stephanie L. Hyland; et al. (CoRR, 2024)

PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation. - Daniel C. Castro; Aurelia Bustos; Shruthi Bannur; Stephanie L. Hyland; Kenza Bouzid; Maria Teodora Wetscherek; M. Sánchez-Valverde; Lara Jaques-Pérez; Lourdes Pérez-Rodríguez; Kenji Takeda; José María Salinas; Javier Alvarez-Valle; et al. (CoRR, 2024)

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 C. Castro; Anton Schwaighofer; Matthew P. Lungren; Maria Teodora Wetscherek; Noel Codella; et al. (Nat. Mac. Intell., 2025)

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 L. Hyland (CoRR, 2025)