An AI tool developed by a team of researchers at Los Angeles-based Cedars-Sinai Health Sciences University can perform genetic profiling faster and at a lower cost compared to conventional methods, according to a study published May 8 in Cell.
Called Path2Space, the tool predicts spatial gene expression using thin slices of cancer tumor tissue viewed through digital images of biopsy slides. Path2Space was trained on breast cancer patient data and validated on three additional patient datasets.
The tool can be trained on and applied to other cancer types, and is designed to inform treatment decisions and patient risk, according to a May 8 news release from Cedars-Sinai.
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