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Since I became NIH Director last year, one key principle has guided my vision and approach: Our work is not finished when we deliver scientific discoveries; our work is finished when all people are living long and healthy lives. But unfortunately, we’re seeing some alarming trends in the health of the U.S. population. It’s a bit of a puzzle. On one hand, significant advances in biomedical research over the last several decades have led to lifesaving interventions for a range of diseases and conditions. At the same time, the overall health of the people in this country appears to be stalled and even getting worse.

NIH Director's Blog OCT. 3, 2024

AI Model Takes New Approach to Performing Diagnostic Tasks in Multiple Cancer Types

In recent years, medical researchers have been looking for ways to use artificial intelligence (AI) technology for diagnosing cancer. So far, most AI models have been developed to perform specific tasks in cancer diagnosis, such as detecting cancer presence or predicting a tumor’s genetic profile in certain cancer types. But what if an AI system could be more flexible, like a large language model such as ChatGPT, performing a variety of diagnostic tasks across multiple cancer types? As reported in the journal Nature, researchers have developed an AI system that can perform a wide range of cancer evaluation tasks and outperforms current AI methods in tasks like cancer cell detection and tumor origin identification. It was tested on 19 cancer types, leading the researchers to refer to it as “ChatGPT-like” in its flexibility. According to the research team, whose work is supported in part by NIH, this is also the first AI model based on analyzing slide images to not only accurately predict if a cancer is likely to respond to treatment, but also to validate these predictions across multiple patient groups around the world.