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AI tool predicts chronic pain risk for breast cancer patients

by Theinsightpost
July 31, 2024
in Science
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AI tool predicts chronic pain risk for breast cancer patients

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A new study uses artificial intelligence to predict which breast cancer patients are most at risk for developing chronic pain.

A third of cancer patients face chronic pain—a debilitating condition that can dramatically reduce a person’s quality of life, even if their cancer goes into remission.

Although doctors have some tools for addressing chronic pain, figuring out who is most at risk for developing it is no easy feat.

The new predictive model could help doctors address underlying conditions that contribute to making pain chronic and ultimately lead to more effective treatments.

“We want to understand the factors that lead someone from having cancer to having chronic pain and how can we better manage these factors,” says Lisiane Pruinelli, a professor of family, community, and health systems science in the University of Florida College of Nursing, and senior author of the study in the Journal of Nursing Scholarship.

“Our goal is to link this information to some profile of patients so we can identify early on what patients are at risk for developing chronic pain.”

The findings from the study show that, when built with detailed data on more than 1,000 breast cancer patients, the AI model could correctly predict which patients would develop chronic pain more than 80% of the time. The leading factors associated with chronic pain included anxiety and depression, previous cancer diagnoses, and certain infections.

Implementing a model like this in doctors’ offices would require integrating it into the electronic healthcare records systems that are now ubiquitous in clinics, which would take more research. The researchers say the rise of AI has the potential to help doctors tailor their treatments to a patient’s unique disease characteristics.

“Now with the amount of data we have, and with the use of artificial intelligence, we can actually personalize treatments based on patient needs and how they would respond to that treatment,” Pruinelli says.

The researchers based the study on the large amount of data made available by the All of Us Research Program, a nationwide research campaign from the National Institutes of Health that seeks to collect anonymized health care records from 1 million Americans.

“This wouldn’t be possible if we didn’t have people contributing their data,” Pruinelli says.

Additional coauthors are from the University of Florida; the University of California, Irvine; and the University of Minnesota.

Source: University of Florida

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