Researchers have developed and tested a new AI tool called Foresight which recognises complex patterns in health data to gain insights and offer predictions of the future health of patients.
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 real-life events as described in patients’ records.
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.
Professor Andrew Morris, Director of HDR UK, said: “AI has immense potential to enable scientific discovery, support the prevention, diagnosis and treatment of disease, and improve care pathway management and education. This work demonstrates the potential that using electronic health records and the latest advancements in AI could deliver for improving clinical decision making. But this is all dependent on the quality and representativeness of data. Sustained investment in the UK’s data infrastructure is needed to enable this in safe and secure ways to maintain privacy and anonymity of people’s health data.
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