A new AI platform tells doctors which past experiences it is using to draw its conclusions. (Credit: Duke University)

An artificial intelligence (AI) platform analyzes potentially cancerous lesions in mammography scans to determine whether a patient should receive an invasive biopsy. But unlike its many predecessors, this algorithm is interpretable, meaning it shows physicians exactly how it came to its conclusions.

The researchers trained the AI to locate and evaluate lesions just like an actual radiologist would be trained, rather than allowing it to freely develop its own procedures, giving it several advantages over its “black box” counterparts. It could make for a useful training platform to teach students how to read mammography images. It could also help physicians in sparsely populated regions around the world who do not regularly read mammography scans make better healthcare decisions.

They first taught the AI to find the suspicious lesions in question and ignore all the healthy tissue and other irrelevant data. Then they hired radiologists to carefully label the images to teach the AI to focus on the edges of the lesions, where the potential tumors meet healthy surrounding tissue, and compare those edges to edges in images with known cancerous and benign outcomes.

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