UNITED KINGDOM: Artificial intelligence (AI) has made yet another breakthrough in healthcare. An AI tool created by researchers can forecast the likelihood of pancreatic cancer up to three years in the future, raising hopes for early identification and better survival rates.
Pancreatic cancer is a particularly aggressive form of cancer, with diagnosis often occurring later when treatment options are limited, and the probability of survival is low. According to the American Cancer Society, only about 10% of people with pancreatic cancer survive for five years or more after diagnosis. Therefore, an early diagnosis is critical for improving the prognosis of patients.
In a study published in the journal Nature Medicine, researchers have shown that an AI algorithm can predict the likelihood of pancreatic cancer by analysing the medical records of millions of patients from Denmark and the United States. The model used disease codes and timing to identify high-risk individuals.
“The ability to identify those at high risk of pancreatic cancer could improve clinical decision-making, leading to earlier diagnosis, treatment, and better outcomes,” said Chris Sander, one of the researchers from the Department of Systems Biology at Harvard Medical School.
The researchers trained the AI algorithm on the medical records of six million patients from Denmark and three million from the United States. The model was then tested on a separate dataset of patients and found to be as accurate as current genetic sequencing tests.
Pancreatic cancer is a major cause of cancer-related deaths worldwide, with increasing incidence. Early detection and diagnosis are crucial to improving survival rates. With this new AI tool, doctors may be able to identify high-risk patients earlier and begin treatment sooner, potentially saving lives.
This breakthrough is just one of many examples of how AI is transforming the healthcare industry. From predicting disease risk to developing personalised treatment plans, AI revolutionises healthcare and improves patient outcomes.
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