The study was led by researchers at Harvard Medical School and the University of Copenhagen in collaboration with VA Boston Healthcare System, the Dana-Farber Cancer Institute and the Harvard T.H. Chan School of Public Health.

A recent study suggests that an AI tool can predict the risk of pancreatic cancer up to three years in advance by analyzing patients’ medical records. The study used an AI-based population screening method that helps identify a specific biomarker of certain diseases, which can be difficult to catch in the early stages.

The researchers applied an AI algorithm to clinical data from nine million patients from Denmark and the US, and trained the AI learning models to read diagnosis codes in the patient’s data and connect them to pancreatic cancer. The AI models were tested for potential diagnosis at different times and were substantially more accurate than current population-wide estimates of disease incidence. (Nature Medicine)

The study was published in the journal Nature Medicine and led by investigators at Harvard Medical School and the University of Copenhagen in collaboration with VA Boston Healthcare System, the Dana-Farber Cancer Institute and the Harvard T.H. Chan School of Public Health.

The early detection of pancreatic cancer is challenging as the cancer often does not show up on imaging tests, leading to a low five-year relative survival rate. Therefore, an AI tool that can identify those at high risk of the disease could go a long way towards improving clinical decision-making.

The study supervisor, Søren Brunak, a professor of disease systems biology at the University of Copenhagen, believes that AI-based screening is an opportunity to alter the trajectory of pancreatic cancer, an aggressive disease that is notoriously hard to diagnose early and treat promptly when the chances for success are highest.

However, the technology is still in its early stages and requires further testing.

The potential benefits of an AI tool that can identify those at high risk of pancreatic cancer include reducing healthcare costs and improving patient outcomes.

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