Using Machine Learning to assess Covid-19 risks (original) (raw)

ABSTRACT: IMPORTANCE: Identifying potential Covid-19 patients in the general population is a huge challenge at the moment. Given the low availability of infected Covid-19 patients clinical data, it is challenging to understand and comprehend similar and complex patterns in these symptomatic patients. Laboratory testing for Covid19 antigen with RT-PCR | (Reverse Transcriptase) is not possible or economical for whole populations. OBJECTIVE: To develop a Covid risk stratifier model that classifies people into different risk cohorts, based on their symptoms and validate the same. DESIGN: Analysis of Covid cases across Wuhan and New York were done to identify the course of these cases prior to being symptomatic and being hospitalised for the infection. A dataset based on these statistics were generated and was then fed into an unsupervised learning algorithm to reveal patterns and identify similar groups of people in the population. Each of these cohorts were then classified and identifi...