Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. - Natalia Antropova; Andrew L. Beam; Brett K. Beaulieu-Jones; Irene Chen; Corey Chivers; Adrian V. Dalca; Samuel G. Finlayson; Madalina Fiterau; Jason Alan Fries; Marzyeh Ghassemi; Mike Hughes; Bruno Jedynak; et al. (CoRR, 2018)

DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis. - Yang Yang 125; Timothy M. Walker; A. Sarah Walker; Daniel J. Wilson 001; Timothy E. A Peto; Derrick W. Crook; Farah Shamout; CRyPTIC Consortium; Tingting Zhu 001; David A. Clifton (Bioinform., 2019)

Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality. - Pulkit Sharma; Farah E. Shamout; David A. Clifton (CoRR, 2019)

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. - Farah E. Shamout; Yiqiu Shen; Nan Wu; Aakash Kaku; Jungkyu Park 001; Taro Makino; Stanislaw Jastrzebski; Duo Wang; Ben Zhang; Siddhant Dogra; Meng Cao; Narges Razavian; et al. (CoRR, 2020)

Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre study. - Ghadeer O. Ghosheh; Bana Alamad; Kai-Wen Yang; Faisil Syed; Nasir Hayat; Imran Iqbal; Fatima Al Kindi; Sara Al Junaibi; Maha Al Safi; Raghib Ali; Walid Zaher; Mariam Al Harbi; et al. (CoRR, 2020)

Deep Interpretable Early Warning System for the Detection of Clinical Deterioration. - Farah E. Shamout; Tingting Zhu 001; Pulkit Sharma; Peter J. Watkinson; David A. Clifton (IEEE J. Biomed. Health Informatics, 2020)

Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest Radiographs. - Nasir Hayat; Hazem Lashen; Farah E. Shamout (MLHC, 2021)

The strategic pursuit of artificial intelligence in the United Arab Emirates. - Farah E. Shamout; Dana Abu Ali (Commun. ACM, 2021)

Explainability Matters: Backdoor Attacks on Medical Imaging. - Munachiso Nwadike; Takumi Miyawaki; Esha Sarkar; Michail Maniatakos; Farah Shamout (CoRR, 2021)

COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. - Anuroop Sriram; Matthew J. Muckley; Koustuv Sinha; Farah Shamout; Joelle Pineau; Krzysztof J. Geras; Lea Azour; Yindalon Aphinyanaphongs; Nafissa Yakubova; William Moore (CoRR, 2021)

Multi-Label Generalized Zero Shot Learning for the Classification of Disease in Chest Radiographs. - Nasir Hayat; Hazem Lashen; Farah E. Shamout (CoRR, 2021)

Meta-repository of screening mammography classifiers. - Benjamin Stadnick; Jan Witowski; Vishwaesh Rajiv; Jakub Chledowski; Farah E. Shamout; Kyunghyun Cho; Krzysztof J. Geras (CoRR, 2021)

Towards dynamic multi-modal phenotyping using chest radiographs and physiological data. - Nasir Hayat; Krzysztof J. Geras; Farah E. Shamout (CoRR, 2021)

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. - Farah E. Shamout; Yiqiu Shen; Nan Wu; Aakash Kaku; Jungkyu Park 001; Taro Makino; Stanislaw Jastrzebski; Jan Witowski; Duo Wang; Ben Zhang; Siddhant Dogra; Meng Cao; et al. (npj Digit. Medicine, 2021)

An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates. - David Johnson; Mohammad Alsharid; Rasheed El-Bouri; Nigel Mehdi; Farah Shamout; Alexandre Szenicer; David Toman 003; Saqr Binghalib (AAAI, 2022)

MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images. - Nasir Hayat; Krzysztof J. Geras; Farah E. Shamout (MLHC, 2022)

Deterioration Prediction using Time-Series of Three Vital Signs and Current Clinical Features Amongst COVID-19 Patients. - Sarmad Mehrdad; Farah E. Shamout; Yao Wang 001; Seyed Farokh Atashzar (CoRR, 2022)

Data Pre-Processing Using Neural Processes for Modeling Personalized Vital-Sign Time-Series Data. - Pulkit Sharma; Farah E. Shamout; Vinayak Abrol; David A. Clifton (IEEE J. Biomed. Health Informatics, 2022)

Privacy-Preserving Machine Learning for Healthcare: Open Challenges and Future Perspectives. - Alejandro Guerra-Manzanares; L. Julian Lechuga Lopez; Michail Maniatakos; Farah E. Shamout (TML4H, 2023)

Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data. - Yiqiu Shen; Jungkyu Park 001; Frank Yeung; Eliana Goldberg; Laura Heacock; Farah Shamout; Krzysztof J. Geras (CoRR, 2023)

Informative Priors Improve the Reliability of Multimodal Clinical Data Classification. - L. Julian Lechuga Lopez; Tim G. J. Rudner; Farah E. Shamout (CoRR, 2023)

Multi-modal Masked Siamese Network Improves Chest X-Ray Representation Learning. - Saeed Shurrab; Alejandro Guerra-Manzanares; Farah E. Shamout (CoRR, 2024)

The Role of Functional Muscle Networks in Improving Hand Gesture Perception for Human-Machine Interfaces. - Costanza Armanini; Tuka Alhanai; Farah E. Shamout; Seyed Farokh Atashzar (CoRR, 2024)

Multimodal Machine Learning for Stroke Prognosis and Diagnosis: A Systematic Review. - Saeed Shurrab; Alejandro Guerra-Manzanares; Amani Magid; Bartlomiej Piechowski-Jozwiak; Seyed Farokh Atashzar; Farah E. Shamout (IEEE J. Biomed. Health Informatics, 2024)

MedMod: Multimodal Benchmark for Medical Prediction Tasks with Electronic Health Records and Chest X-Ray Scans. - Shaza Elsharief; Saeed Shurrab; Baraa Al Jorf; Leopoldo Julian Lechuga López; Krzysztof J. Geras; Farah E. Shamout (CHIL, 2025)

Uncertainty Quantification for Machine Learning in Healthcare: A Survey. - Leopoldo Julian Lechuga López; Shaza Elsharief; Dhiyaa Al Jorf; Firas Darwish; Congbo Ma; Farah E. Shamout (CHIL, 2025)

MIND: Modality-Informed Knowledge Distillation Framework for Multimodal Clinical Prediction Tasks. - Alejandro Guerra-Manzanares; Farah Shamout (Trans. Mach. Learn. Res., 2025)

Multimodal Deep Learning for Stroke Prediction and Detection using Retinal Imaging and Clinical Data. - Saeed Shurrab; Aadim Nepal; Terrence J. Lee-St. John; Nicola G. Ghazi; Bartlomiej Piechowski-Jozwiak; Farah E. Shamout (CoRR, 2025)

MedArabiQ: Benchmarking Large Language Models on Arabic Medical Tasks. - Mouath Abu Daoud; Chaimae Abouzahir; Leen Kharouf; Walid Al-Eisawi; Nizar Habash; Farah E. Shamout (CoRR, 2025)