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Study: AI can predict pancreatic cancer three years ahead of human doctors

We chat to one of the Harvard Medical School researchers involved

AI algorithms can screen for pancreatic cancer and predict whether patients will develop the disease up to three years before a human doctor can make the same diagnosis, according to research published in Nature on Monday.

Pancreatic cancer is deadly; the five-year survival rate averages 12 percent. Academics working in Denmark and the US believe AI could help clinicians by detecting pancreatic cancer at earlier stages, if the software can reliably predict which patients are at higher risk of developing the disease. 

The researchers trained AI algorithms on millions of medical records obtained in the Danish National Patient Registry and the US Veterans Affairs Corporate Data Warehouse. The models were trained to correlate diagnosis codes – labels used by hospitals describing different medical conditions – to pancreatic cancer.

Some diagnosis codes for jaundice, abdominal and pelvic pain, weight loss, for example, are more closely related to the disease – especially if they are found in patients about six months before diagnosis – while others like Type 2 diabetes, anemia, or inflammation of the pancreas are usually found earlier.

"Cancer gradually develops in the human body, often over many years and fairly slowly, until the disease takes hold," Chris Sander, the study's co-senior investigator and leader of a lab working at the Department of Systems Biology at Harvard Medical School, told The Register.

"The AI system attempts to learn from signs in the human body that may relate to such gradual changes."

"But it is early days for this, and while the AI system can make reasonably accurate predictions, it cannot, or not currently, identify mechanisms or causative events. Like often in science, correlation is useful for prediction, but causation is much harder to establish," he said.

The most effective model, based on a transformer-based architecture, showed that out of the top 1,000 highest-risk patients over 50, about 320 would go on to develop pancreatic cancer. The model is less accurate when trying to predict pancreatic cancer over longer time intervals compared to shorter ones, and for patients younger than 50.

"AI on real-world clinical records has the potential to produce a scalable workflow for early detection of cancer in the community, to shift focus from treatment of late-stage to early-stage cancer, to improve the quality of life of patients and to increase the benefit/cost ratio of cancer care," the paper reads.

Effective prediction in real-world settings will rely on the quality of patients' medical histories. Future AI-based screening tools for pancreatic cancer will have to be trained on specific local population data, the study found. A model trained on data from Danish patients, for example, was not as accurate when applied to US patients. 

"Given the experience in Denmark and one or two US health systems, this means that in each country with different conditions and different systems, it is best to re-train the model locally. AI needs a lot of data to train. Access in different locations is not straightforward, as medical records are and should be confidential. So local approval and data security is essential," Sander said.

The study is still in its early stages, and the software cannot yet be used to run screening programs. Improvements are needed before even a trial can be conducted. 

"Once a surveillance program is implemented, the actual computing costs for applying the software are moderate. The training is what consumes considerable computing resources. The actual clinical tests to see early signs of cancer or to detect cancer when it is still very small are costly, much more expensive than for example mammograms," Sander added. 

Still, the team believes that as the technology improves and operating costs decrease, AI could become a valuable screening tool in the future. 

"Many types of cancer, especially those hard to identify and treat early, exert a disproportionate toll on patients, families and the healthcare system as a whole," said Søren Brunak, professor of disease systems biology and director of research at the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen, a co-senior investigator of the study, said in a statement. 

"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," he concluded. ®

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