AI Model Offers New Weapon Against Hard-to-Treat Cancers
Researchers have developed a 'symbolic AI' model to predict effective treatments for Triple-Negative Breast Cancer by analyzing genetic fingerprints. Unlike traditional 'black box' AI, this logic-based approach allows doctors to understand the reasoning behind treatment recommendations.
Why it matters
This advancement offers a more transparent and reliable tool for personalized medicine, potentially improving outcomes for patients with aggressive, hard-to-treat cancers.
In a new paper published in Cell Reports Medicine, the UCL team outline how they, in collaboration with a University of Cambridge team, developed a new type of treatment-predicting computer program that uses an individual's detailed genetic fingerprint to explore which treatments, if any, may kill their cancer - especially when standard treatments have failed.
Computer models have long been used in cancer medicine and more recently artificial intelligence has opened up a whole new avenue in this regard.
But the "black box" nature of 'traditional' AI associated with Large Language Models - where how they arrive at their conclusions is unclear - has prompted a degree of scepticism among the medical profession, the researchers said.
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