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Source: Medical Innovations  Jul 20, 2020  3 years, 8 months, 4 weeks, 18 hours, 46 minutes ago

Medical Innovations: Want To Know If You Will Die From COVID-19? Check Out MIT’s Online COVID-19 Mortality Risk Calculator

Medical Innovations: Want To Know If You Will Die From COVID-19? Check Out MIT’s Online COVID-19 Mortality Risk Calculator
Source: Medical Innovations  Jul 20, 2020  3 years, 8 months, 4 weeks, 18 hours, 46 minutes ago
Medical Innovations: Researchers led by Massachusetts Institute of Technology along with colleagues from University of Seville-Spain, Benefits Science Technologies-Boston, Hartford HealthCare-Connecticit, Azienda Socio-Sanitaria Territoriale di Cremona-Italy and HM Hospitals Spain have created a new online COVID-19 Mortality Risk calculator for all healthcare  professionals and even laymen to use. The researchers had even conducted a detailed assessment and study of its practicality.


 
The COVID-19 Mortality Risk Calculator or CMR is accessible through this link: https://covidanalytics.io/mortality_calculator
 
To date, the COVID-19 pandemic has been wreaking havoc for over six months, causing over 14.6 million cases and over 607,150 deaths. Caused by the SARS-CoV-2 coronavirus, it has stimulated intense research to pinpoint its risk factors and modes of spread. This would significantly improve the management of patients at all stages. However, the lack of adequate data and the speed with which the disease is spreading has made the process difficult.
 
This new study describes the use of machine learning and AI (artificial Intelligence) to provide a better understanding of the risk factors in large and mixed groups. The use of algorithms can help objectively evaluate these factors and perhaps capture interactions that could be missed in a purely observational study.
 
The research findings are published on a preprint server and have yet to have been peer-reviewed.
https://www.medrxiv.org/content/10.1101/2020.07.07.20148304v3
 
The study presents the COVID-19 Mortality Risk (CMR) tool, which is a new machine learning model meant to predict the death rate in hospitalized patients with COVID-19. This would help deliver care to patients in a system where the resources are limited by enabling individualized risk scoring. The data is taken from many centers in the US and Europe and includes demographics, laboratory results, and coexisting illnesses.
 
The study team used the XGBoost algorithm, which is a machine ensemble learning method that can be used to predict probability. CERN recognized it as the best approach to classify signals from the Large Hadron Collider. The ability of XGBoost to capture nonlinear risk factors leads to robust predictive performance. The researchers also found that the commonly accepted risk factors like age and poor lung oxygenation were indeed associated with a high risk.
 
The research first considered an international cohort admitted across three hospitals in Spain, Italy, and the US. The cohort was then tested for validity on hospitalized patients in a six-hospital group based in Greece, Spain, and the US. This would ensure that both the patient profiles and the mortality rates are widely varied.
 
The present model is an advance versionon an earlier model proposed by Pourhomayoun et al. (2020), which was not comprehensive in the scope of the patient data. In this study the final population was over 3,000 patients, with an observed death percentage of abou