Analysis submitted for the American Diabetes Association’s 83rd Scientific Sessions, San Diego, June 23–26, 2023

A Neural Network Model for the Prediction of Comorbid Cardiometabolic Diseases: Proof of Concept using UK Primary Care Data

Andrew Krentz, Lucas Brunschwig, Yaron Dibner, Hugo Michel, André Jaun

This proof-of-concept analysis demonstrates the utility of a neural network to predict the development of one or more comorbidities based on data routinely collected in primary care. At the level of individual patients knowledge of the probability of acquiring additional comorbidities could provide opportunities for prevention. Non-pharmacological and specific pharmacological interventions could be directed at avoiding or postponing additional cardiometabolic risk factors.

Read the article here: