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New Tool Helps Predict the Mortality Risk of Coronavirus

New Tool Helps Predict the Mortality Risk of Coronavirus

UK-based company i5 has launched a free Risk Calculator for Predicting the Mortality Risk of Coronavirus.

The new tool that can be accessed at https://coronavirusrisk.org uses past medical history of people to predict their mortality rates if infected by the virus 2019-nCoV leading to the respiratory condition Covid-19.

Individuals, as well as Public Health authorities, Governments and Clinicians, can use the prediction tool to assess the mortality risk of people, with or without Covid-19:

The Coronavirus Mortality Risk Calculator portal allows individuals to enter past medical history that is relevant for the mortality risk prediction. For high volume data processing, a REST API is available from i5 Analytics for public health authorities and governments.

By supporting the identification of people at higher risk and special populations either by individuals themselves or through the use of pseudonymised data, the disease progression of 2019-nCoV globally can be greatly reduced.

A scientific publication about the AI used for Covid-19 mortality risk prediction is available here.

I5’s AI is based on neural networks and is trained and tested on millions of medical records and can be used for screening programmes, hospital optimisation, reducing complications and disease prevention programmes.

I5, is a leader in the application of healthcare artificial Intelligence, the company’s IT solutions combine healthcare data and AI to provide preliminary diagnosis, outcome prediction, service recommendations and health economy planning. Those systems are trained on several billions of NHS records and are eminently applicable to WHO member countries around the world.

The origins and a lot of the methodology behind the Risk Calculator are to be found in the company’s Diagnosis Stratification (i5 DST) tool – which is an algorithm-based Artificial Intelligence clinical evaluation tool that can identify undiagnosed patients with a high likelihood of having a long term condition.

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