Farah Shamout

According to our database, Farah Shamout authored at least 41 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records.

Saeed Shurrab, Mariam Al-Omari, Dana El Samad, Farah E. Shamout

CoRR, May, 2026

AgentRx: A Benchmark Study of LLM Agents for Multimodal Clinical Prediction Tasks.

Baraa Al Jorf, Farah E. Shamout

CoRR, May, 2026

Data-Driven Priors for Uncertainty-Aware Deterioration Risk Prediction with Multimodal Data.

L. Julián Lechuga López, Tim G. J. Rudner, Farah E. Shamout

CoRR, March, 2026

An Empirical Analysis of Calibration and Selective Prediction in Multimodal Clinical Condition Classification.

Leopoldo Julian Lechuga López, Farah E. Shamout, Tim G. J. Rudner

CoRR, March, 2026

Position Paper: Artificial Intelligence in Medical Image Analysis: Advances, Clinical Translation, and Emerging Frontiers.

Andreas S. Panayides, Hao Chen, Nenad D. Filipovic, Tijana Geroski, Junlin Hou, Karim Lekadir, Kostas Marias, George K. Matsopoulos, Giorgos Papanastasiou, Pinaki Sarder, Georgia D. Tourassi, Sotirios A. Tsaftaris, Huazhu Fu, Efthyvoulos C. Kyriacou, Christos P. Loizou, Michalis E. Zervakis, Joel H. Saltz, Farah E. Shamout, Ken C. L. Wong, Jianhua Yao, Amir A. Amini, Dimitrios I. Fotiadis, Constantinos S. Pattichis, Marios S. Pattichis

IEEE J. Biomed. Health Informatics, February, 2026

MedErrBench: A Fine-Grained Multilingual Benchmark for Medical Error Detection and Correction with Clinical Expert Annotations.

Congbo Ma, Yichun Zhang, Yousef Al-Jazzazi, Ahamed Foisal, Laasya Sharma, Yousra Sadqi, Khaled Saleh, Jihad Mallat, Farah E. Shamout

CoRR, February, 2026

Cross-Lingual Empirical Evaluation of Large Language Models for Arabic Medical Tasks.

Chaimae Abouzahir, Congbo Ma, Nizar Habash, Farah E. Shamout

CoRR, February, 2026

MedAraBench: Large-Scale Arabic Medical Question Answering Dataset and Benchmark.

Mouath Abu Daoud, Leen Kharouf, Omar El Hajj, Dana El Samad, Mariam Al-Omari, Jihad Mallat, Khaled Saleh, Nizar Habash, Farah E. Shamout

CoRR, February, 2026

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, May, 2025

MIND: Modality-Informed Knowledge Distillation Framework for Multimodal Clinical Prediction Tasks.

Alejandro Guerra-Manzanares, Farah Shamout

Trans. Mach. Learn. Res., 2025

AraHealthQA 2025: The First Shared Task on Arabic Health Question Answering.

Hassan Alhuzali, Farah E. Shamout, Muhammad Abdul-Mageed, Chaimae Abouzahir, Mouath Abu Daoud, Ashwag Alasmari, Walid Al-Eisawi, Renad Al-Monef, Ali Alqahtani, Lama Ayash, Nizar Habash, Leen Kharouf

Proceedings of The Third Arabic Natural Language Processing Conference: ArabicNLP 2025, 2025

MedPatch: Confidence-Guided Multi-Stage Fusion for Multimodal Clinical Data.

Baraa Al Jorf, Farah E. Shamout

Proceedings of the Machine Learning for Healthcare Conference (MLHC 2025), 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

Proceedings of the Machine Learning for Healthcare Conference (MLHC 2025), 2025

Meta-Repository of Screening Mammography Classifiers.

Jakub Chledowski, Benjamin Stadnick, Jan Witowski, Vishwaesh Rajiv, Farah E. Shamout, Kyunghyun Cho, Krzysztof J. Geras

Proceedings of the MEDINFO 2025 - Healthcare Smart × Medicine Deep, 2025

MILES: Modality-Informed Learning Rate Scheduler for Balancing Multimodal Learning.

Alejandro Guerra-Manzanares, Farah E. Shamout

Proceedings of the International Joint Conference on Neural Networks, 2025

BlendFL: Blended Federated Learning for Handling Multimodal Data Heterogeneity.

Alejandro Guerra-Manzanares, Omar El-Herraoui, Michail Maniatakos, Farah E. Shamout

Proceedings of the International Joint Conference on Neural Networks, 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

Proceedings of the Conference on Health, 2025

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

Proceedings of the Conference on Health, 2025

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, November, 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

Multi-modal Masked Siamese Network Improves Chest X-Ray Representation Learning.

Saeed Shurrab, Alejandro Guerra-Manzanares, Farah E. Shamout

CoRR, 2024

2023

Informative Priors Improve the Reliability of Multimodal Clinical Data Classification.

L. Julián Lechuga López, Tim G. J. Rudner, Farah E. Shamout

CoRR, 2023

Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data.

Yiqiu Shen, Jungkyu Park, Frank Yeung, Eliana Goldberg, Laura Heacock, Farah Shamout, Krzysztof J. Geras

CoRR, 2023

Privacy-Preserving Machine Learning for Healthcare: Open Challenges and Future Perspectives.

Alejandro Guerra-Manzanares, L. Julián Lechuga López, Michail Maniatakos, Farah E. Shamout

Proceedings of the Trustworthy Machine Learning for Healthcare, 2023

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

Deterioration Prediction using Time-Series of Three Vital Signs and Current Clinical Features Amongst COVID-19 Patients.

Sarmad Mehrdad, Farah E. Shamout, Yao Wang, Seyed Farokh Atashzar

CoRR, 2022

MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images.

Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout

Proceedings of the Machine Learning for Healthcare Conference, 2022

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, Saqr Binghalib

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

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, Taro Makino, Stanislaw Jastrzebski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras

npj Digit. Medicine, 2021

Towards dynamic multi-modal phenotyping using chest radiographs and physiological data.

Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout

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

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

Explainability Matters: Backdoor Attacks on Medical Imaging.

Munachiso Nwadike, Takumi Miyawaki, Esha Sarkar, Michail Maniatakos, Farah Shamout

CoRR, 2021

The strategic pursuit of artificial intelligence in the United Arab Emirates.

Farah E. Shamout, Dana Abu Ali

Commun. ACM, 2021

Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest Radiographs.

Nasir Hayat, Hazem Lashen, Farah E. Shamout

Proceedings of the Machine Learning for Healthcare Conference, 2021

2020

Deep Interpretable Early Warning System for the Detection of Clinical Deterioration.

Farah E. Shamout, Tingting Zhu, Pulkit Sharma, Peter J. Watkinson, David A. Clifton

IEEE J. Biomed. Health Informatics, 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, Farah E. Shamout

CoRR, 2020

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, Taro Makino, Stanislaw Jastrzebski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras

CoRR, 2020

2019

Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality.

Pulkit Sharma, Farah E. Shamout, David A. Clifton

CoRR, 2019

DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis.

Yang Yang, Timothy M. Walker, A. Sarah Walker, Daniel J. Wilson, Timothy E. A Peto, Derrick W. Crook, Farah Shamout, CRyPTIC Consortium, Tingting Zhu, David A. Clifton

Bioinform., 2019

2018

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, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi

CoRR, 2018