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2020 – today
- 2024
[i17]Saeed Shurrab, Alejandro Guerra-Manzanares, Farah E. Shamout:
Multi-modal Masked Siamese Network Improves Chest X-Ray Representation Learning. CoRR abs/2407.04449 (2024)- [i16]Costanza Armanini, Tuka Alhanai, Farah E. Shamout, Seyed Farokh Atashzar:
The Role of Functional Muscle Networks in Improving Hand Gesture Perception for Human-Machine Interfaces. CoRR abs/2408.02547 (2024) - 2023
- [c4]Alejandro Guerra-Manzanares
, L. Julian Lechuga Lopez, Michail Maniatakos, Farah E. Shamout:
Privacy-Preserving Machine Learning for Healthcare: Open Challenges and Future Perspectives. TML4H 2023: 25-40 - [i15]Alejandro Guerra-Manzanares, L. Julian Lechuga Lopez, Michail Maniatakos, Farah E. Shamout:
Privacy-preserving machine learning for healthcare: open challenges and future perspectives. CoRR abs/2303.15563 (2023) - [i14]Yiqiu Shen, Jungkyu Park, Frank Yeung, Eliana Goldberg, Laura Heacock, Farah Shamout, Krzysztof J. Geras:
Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data. CoRR abs/2311.03217 (2023) - [i13]L. Julian Lechuga Lopez, Tim G. J. Rudner, Farah E. Shamout:
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification. CoRR abs/2312.00794 (2023) - 2022
- [j5]Pulkit Sharma, Farah E. Shamout, Vinayak Abrol, David A. Clifton:
Data Pre-Processing Using Neural Processes for Modeling Personalized Vital-Sign Time-Series Data. IEEE J. Biomed. Health Informatics 26(4): 1528-1537 (2022) - [c3]David Johnson, Mohammad Alsharid, Rasheed El-Bouri, Nigel Mehdi, Farah Shamout, Alexandre Szenicer, David Toman, Saqr Binghalib:
An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates. AAAI 2022: 12766-12773 - [c2]Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout:
MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images. MLHC 2022: 479-503 - [i12]David Johnson, Mohammad Alsharid, Rasheed El-Bouri, Nigel Mehdi, Farah Shamout, Alexandre Szenicer, David Toman, Saqr Binghalib:
An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates. CoRR abs/2202.01281 (2022) - [i11]Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout:
MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images. CoRR abs/2207.07027 (2022) - [i10]Sarmad Mehrdad, Farah E. Shamout, Yao Wang, Seyed Farokh Atashzar:
Deterioration Prediction using Time-Series of Three Vital Signs and Current Clinical Features Amongst COVID-19 Patients. CoRR abs/2210.05881 (2022) - 2021
- [j4]Farah E. Shamout, Dana Abu Ali:
The strategic pursuit of artificial intelligence in the United Arab Emirates. Commun. ACM 64(4): 57-58 (2021) - [j3]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:
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. npj Digit. Medicine 4 (2021) - [c1]Nasir Hayat, Hazem Lashen, Farah E. Shamout:
Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest Radiographs. MLHC 2021: 461-477 - [i9]Munachiso Nwadike, Takumi Miyawaki, Esha Sarkar, Michail Maniatakos, Farah Shamout:
Explainability Matters: Backdoor Attacks on Medical Imaging. CoRR abs/2101.00008 (2021) - [i8]Anuroop Sriram, Matthew J. Muckley, Koustuv Sinha, Farah Shamout, Joelle Pineau, Krzysztof J. Geras, Lea Azour, Yindalon Aphinyanaphongs, Nafissa Yakubova, William Moore:
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. CoRR abs/2101.04909 (2021) - [i7]Nasir Hayat, Hazem Lashen, Farah E. Shamout:
Multi-Label Generalized Zero Shot Learning for the Classification of Disease in Chest Radiographs. CoRR abs/2107.06563 (2021) - [i6]Benjamin Stadnick, Jan Witowski, Vishwaesh Rajiv, Jakub Chledowski, Farah E. Shamout, Kyunghyun Cho, Krzysztof J. Geras:
Meta-repository of screening mammography classifiers. CoRR abs/2108.04800 (2021) - [i5]Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout:
Towards dynamic multi-modal phenotyping using chest radiographs and physiological data. CoRR abs/2111.02710 (2021) - 2020
- [j2]Farah E. Shamout, Tingting Zhu, Pulkit Sharma, Peter J. Watkinson, David A. Clifton:
Deep Interpretable Early Warning System for the Detection of Clinical Deterioration. IEEE J. Biomed. Health Informatics 24(2): 437-446 (2020) - [i4]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:
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. CoRR abs/2008.01774 (2020) - [i3]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:
Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre study. CoRR abs/2012.01138 (2020)
2010 – 2019
- 2019
- [j1]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:
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis. Bioinform. 35(18): 3240-3249 (2019) - [i2]Pulkit Sharma, Farah E. Shamout, David A. Clifton:
Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality. CoRR abs/1912.00354 (2019) - 2018
- [i1]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:
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR abs/1811.07216 (2018)
Coauthor Index
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