Belonging to the same family of AI models as ChatGPT , Foresight uses a Deep Learning approach to recognise complex patterns in both the structured and unstructured data of electronic health records to produce insights and predictions . While ChatGPT uses publicly available information which has not been medically verified , Foresight is trained on information from NHS electronic health records ( EHRs ).

Supported by Health Data Research UK ( HDR UK ), researchers at King ’ s College London , UCL , King ’ s College Hospital NHS Foundation Trust and Guy ’ s and St Thomas ’ NHS Foundation Trust investigated the accuracy of Foresight ’ s medical predictions by comparing them to reallife events as described in patients ’ records .

Zeljko Kraljevic , Research Fellow in Health Informatics , Biostatistics and Health Informatics at King ’ s College London Institute of Psychiatry , Psychology and Neuroscience ( IoPPN ), developed Foresight and is first author on the journal paper . He said : “ Our study shows that Foresight can achieve high levels of precision in predicting health trajectories of patients , demonstrating it could be a valuable tool to aid decision-making and inform clinical research .

“ The proposed purpose of Foresight is not to enable patients to self-diagnose or predict their future , but it could potentially be used as an aid by clinicians to make sure a diagnosis is not missed , or for continual patient monitoring for real-time risk prediction . One of the main advantages of Foresight that it can easily scale to more patients , hospitals or disorders with minimal or no modifications , and the more data it receives , the better it gets .” �

The researchers trained three different models of Foresight using data from over 811,000 patients across King ’ s College Hospital NHS Foundation Trust , South London and Maudsley NHS Foundation Trust and MIMIC-III ( a publicly available dataset of patients from Beth Israel Deaconess Medical Center in the US ). The de-identified data was approved under NHS governance processes with input from patients , and the research was completed inside the hospital NHS firewall to ensure data security .

Researchers extracted and processed the unstructured , or free-text , and structured data within ECRs using CogStack – a tool that processes the free-text information into a format that researchers can use more easily , developed with support from HDR UK .

Published in The Lancet Digital Health , the study found that when forecasting the next diagnosis of a condition in a patient ’ s health record , Foresight achieved a precision rate of 68 % and 76 % in the two datasets from UK NHS Trusts and 88 % in the US MIMIC-III dataset .

When forecasting the next new biomedical ‘ concept ’, which could be a disorder , symptom , relapse or medication , the precision achieved by Foresight was 80 %, 81 % and 91 % respectively .

52 www . intelligenthealth . tech