Search Results for author: Farah E. Shamout

Found 9 papers, 5 papers with code

Privacy-preserving machine learning for healthcare: open challenges and future perspectives

no code implementations27 Mar 2023 Alejandro Guerra-Manzanares, L. Julian Lechuga Lopez, Michail Maniatakos, Farah E. Shamout

Machine Learning (ML) has recently shown tremendous success in modeling various healthcare prediction tasks, ranging from disease diagnosis and prognosis to patient treatment.

Privacy Preserving

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

no code implementations12 Oct 2022 Sarmad Mehrdad, Farah E. Shamout, Yao Wang, S. Farokh Atashzar

This is infeasible for telehealth solutions and highlights a gap in deterioration prediction models that are based on minimal data, which can be recorded at a large scale in any clinic, nursing home, or even at the patient's home.

Time Series Time Series Analysis

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

1 code implementation14 Jul 2021 Nasir Hayat, Hazem Lashen, Farah E. Shamout

Here, we propose a multi-label generalized zero shot learning (CXR-ML-GZSL) network that can simultaneously predict multiple seen and unseen diseases in CXR images.

Generalized Zero-Shot Learning

Clinical prediction system of complications among COVID-19 patients: a development and validation retrospective multicentre study

1 code implementation28 Nov 2020 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

In test set B (225 patient encounters), the respective system achieves 0. 90 AUROC for AKI, elevated troponin, and elevated interleukin-6, and >0. 80 AUROC for most of the other complications.

Model Selection

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

1 code implementation4 Aug 2020 Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanisław Jastrzębski, 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

In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time.

COVID-19 Diagnosis Decision Making +1

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

no code implementations1 Dec 2019 Pulkit Sharma, Farah E. Shamout, David A. Clifton

Machine learning models can be used for pattern recognition in medical data in order to improve patient outcomes, such as the prediction of in-hospital mortality.

Federated Learning

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