Using machine learning algorithms to develop a clinical decision-making tool for COVID-19 inpatients

Background: Within the UK, COVID-19 has contributed towards over 103,000 deaths. Although multiple risk factors for COVID-19 have been identified, using this data to improve clinical care has proven challenging. The main aim of this study is to develop a reliable, multivariable predictive model for...

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Bibliographic Details
Main Authors: Abhinav Vepa, Amer Saleem, Kami Rakhshanbabanari, Alireza Daneshkhah, Tabassom Sedighi, Shamarina Shohaimi, Amr Omar, Nader Salari, Omid Chatrabgoun, Diana Dharmaraj, Junaid Sami, Shital Parekh, Mohamed Ibrahim, Mohammed Raza, Poonam Kapila, Prithwiraj Chakrabarti
Format: Default Article
Published: 2021
Subjects:
Bayesian network
COVID-19
SARS CoV
Random forest
Risk stratification
Synthetic minority oversampling technique (SMOTE)
Online Access:https://hdl.handle.net/2134/25215698.v1
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