Farah Shamout
Farah Shamout
Clinical AI Lab @ NYU Abu Dhabi
Verified email at nyu.edu
Cited by
Cited by
Enhancement of non-invasive trans-membrane drug delivery using ultrasound and microbubbles during physiologically relevant flow
FE Shamout, AN Pouliopoulos, P Lee, S Bonaccorsi, L Towhidi, R Krams, ...
Ultrasound in medicine & biology 41 (9), 2435-2448, 2015
Deep Interpretable Early Warning System for the Detection of Clinical Deterioration
FE Shamout, T Zhu, P Sharma, PJ Watkinson, DA Clifton
IEEE Journal of Biomedical and Health Informatics 24 (2), 437-446, 2020
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department
FE Shamout, Y Shen, N Wu, A Kaku, J Park, T Makino, S Jastrzębski, ...
NPJ digital medicine 4 (1), 1-11, 2021
Machine Learning for Clinical Outcome Prediction
FE Shamout, T Zhu, DA Clifton
IEEE Reviews in Biomedical Engineering, 2020
Early warning score adjusted for age to predict the composite outcome of mortality, cardiac arrest or unplanned intensive care unit admission using observational vital-sign …
F Shamout, T Zhu, L Clifton, J Briggs, D Prytherch, P Meredith, ...
BMJ open 9 (11), e033301, 2019
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
Y Yang, TM Walker, AS Walker, DJ Wilson, TEA Peto, DW Crook, ...
Bioinformatics 35 (18), 3240-3249, 2019
Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality
P Sharma, FE Shamout, DA Clifton
NeurIPS 2019 Workshop AI for Social Good arXiv preprint arXiv:1912.00354, 2019
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction
A Sriram, M Muckley, K Sinha, F Shamout, J Pineau, KJ Geras, L Azour, ...
arXiv preprint arXiv:2101.04909, 2021
Machine learning for health (ML4H) workshop at NeurIPS 2018
N Antropova, AL Beam, BK Beaulieu-Jones, I Chen, C Chivers, A Dalca, ...
arXiv preprint arXiv:1811.07216, 2018
Artificial Intelligence System Reduces False-Positive Findings in the Interpretation of Breast Ultrasound Exams
Y Shen, FE Shamout, JR Oliver, J Witowski, K Kannan, J Park, N Wu, ...
medRxiv, 2021
Development and validation of early warning score systems for COVID-19 patients
A Youssef, S Kouchaki, F Shamout, J Armstrong, R El-Bouri, T Taylor, ...
Healthcare Technology Letters, 1-12, 2021
Explainability Matters: Backdoor Attacks on Medical Imaging
M Nwadike, T Miyawaki, E Sarkar, M Maniatakos, F Shamout
AAAI 2021 Workshop on Trustworthy AI for Healthcare, 2020
Towards dynamic multi-modal phenotyping using chest radiographs and physiological data
N Hayat, KJ Geras, FE Shamout
arXiv preprint arXiv:2111.02710, 2021
Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest Radiographs
N Hayat, H Lashen, FE Shamout
Machine Learning for Healthcare Conference, 461-477, 2021
Data pre-processing using Neural Processes for Modelling Personalised Vital-Sign Time-Series Data
P Sharma, FE Shamout, V Abrol, D Clifton
IEEE Journal of Biomedical and Health Informatics, 2021
Meta-repository of screening mammography classifiers
B Stadnick, J Witowski, V Rajiv, J Chłędowski, FE Shamout, K Cho, ...
arXiv preprint arXiv:2108.04800, 2021
Artificial Intelligence: The New Alexander Fleming
Z Almallah, R El-Lababidi, F Shamout, DJ Doyle
Healthcare informatics research 27 (2), 168-171, 2021
The NYU Breast Ultrasound Dataset v1.0
F Shamout, Y Shen, J Witowski, J Oliver, K Kannan, NW Wu, J Park, ...
https://cs.nyu.edu/~kgeras/reports/ultrasound_datav1.0.pdf, 2021
The strategic pursuit of artificial intelligence in the United Arab Emirates
FE Shamout, DA Ali
Communications of the ACM 64 (4), 57-58, 2021
Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre study
GO Ghosheh, B Alamad, KW Yang, F Syed, N Hayat, I Iqbal, FA Kindi, ...
arXiv preprint arXiv:2012.01138, 2020
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