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Artificial Intelligence Identifies Lung Cancer Patients at Risk of Harm Caused by Immunotherapy

Artificial Intelligence Identifies Lung Cancer Patients at Risk of Harm Caused by Immunotherapy February 9, 2021 In a subset of patients diagnosed with non-small cell lung cancer (NSCLC), immunotherapy paradoxically exacerbates tumor growth and significantly shortens survival. Currently there are no clinically validated biomarkers that can identify patients at risk of this paradoxical response called “hyperprogression.” Using artificial intelligence (AI) analysis of simple tissue scans, researchers at Case Western University claim they have discovered biomarkers that could tell which lung cancer patients might get worse from immunotherapy. In addition to those who would benefit from immunotherapy, and those who might not, researchers and oncologists can now identify a third category of patients called hyper-progressors who would be harmed by the same immunotherapy, says Pranjal Vaidya, a PhD student in biomedical engineering and researcher at the university’s Center for Com

AI Helps to Study Which Cancer Patients Might be Harmed by Immunotherapy

AI Helps to Study Which Cancer Patients Might be Harmed by Immunotherapy Written by AZoRoboticsFeb 5 2021 At Case Western Reserve University, scientists have used artificial intelligence (AI) to analyze simple tissue scans and discovered biomarkers that could pinpoint to doctors those lung cancer patients who might actually suffer worse from immunotherapy. Image credit: Design Cells/shutterstock.com To date, oncologists and scientists had classified these lung cancer patients into two wider categories those who would benefit from immunotherapy, and those who would probably not. However, according to Pranjal Vaidya, a PhD student in biomedical engineering and researcher at the university’s Center for Computational Imaging and Personalized Diagnostics (CCIPD), a third category of patients has started to emerge hyper-progressors who would actually get worse by immunotherapy, such as a very short lifespan following treatment.

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