Research published in Nature Medicine in May suggests that AI screening of large groups of patients could make earlier diagnosis possible, which in turn could lead to earlier and more effective treatment of the disease.
Researchers used data from the medical records of patients in both the United States and Denmark dating from 1977 to 2020. They looked at a group of 6.2 million Danish patients, 23,985 of whom were eventually diagnosed with pancreatic cancer, and 3 million military veterans receiving care through Veterans Affairs, of whom 3,864 were ultimately diagnosed.
Some of the symptoms associated with a higher risk prediction aren’t traditionally linked to pancreatic cancer. Gallstones, Type 2 diabetes, anemia and gastrointestinal symptoms such as vomiting and abdominal pain were all linked to a higher risk score as long as three years before diagnosis. In a real-world scenario, the researchers write, about 320 of every 1,000 people the AI model identified as high risk would go on to develop pancreatic cancer. By targeting surveillance to high-risk patients, the tool could make screening more affordable, they write.
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