AI model calculates percent necrosis in osteosarcoma patients with 99% accuracy

Reviewed by Megan Craig, M.Sc.Nov 3 2023 A research team at Johns Hopkins Medicine has created and trained a machine learning model to calculate percent necrosis -; or, what percentage of a tumor is "dead" and no longer active -; in patients with osteosarcoma, a type of bone cancer. The model's calculation was 85% correct when compared to the results of a musculoskeletal pathologist. Upon removing one outlier, the accuracy rose to 99%.

Christa LiBrizzi, M.D., co-first author of the study and a resident with Johns Hopkins Medicine's Department of Orthopaedic Surgery "We decided to train the model by teaching it to recognize image patterns," says Zhenzhen Wang, co-first author of the study and a doctoral student in biomedical engineering at the Johns Hopkins University School of Medicine. "We segregated the WSIs into thousands of small patches, then divided the patches into groups based on how they were labeled by the pathologist. Finally, we fed these grouped patches into the model to train it.

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