Learning From Past Respiratory Infections to Predict COVID-19 Outcomes: Retrospective Study.

ABSTRACT:

Background

For the clinical care of patients with well-established diseases, randomized trials, literature, and research are supplemented with clinical judgment to understand disease prognosis and inform treatment choices. In the void created by a lack of clinical experience with COVID-19, artificial intelligence (AI) may be an important tool to bolster clinical judgment and decision making. However, a lack of clinical data restricts the design and development of such AI tools, particularly in preparation for an impending crisis or pandemic.

Objective

This study aimed to develop and test the feasibility of a "patients-like-me" framework to predict the deterioration of patients with COVID-19 using a retrospective cohort of patients with similar respiratory diseases.

Method

SUBMITTER: Sang S 

PROVIDER: S-EPMC7901593 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature