Radiology’s cousin ’ology reckons with AI

The same sense of eager anticipation mixed with abject fear that machine learning has been driving into the heart of radiology is piercing pathology too.

F. Perry Wilson, MD, of Yale takes up the technology as poised to transform the latter specialty, which some consider radiology’s closest kin, in a lively blog post spurred by a Dec. 12 JAMA study.

In the study, Dutch researchers found algorithms to be more accurate than pathologists at detecting lymph node metastases when both were held to a completely objective gold standard.

The study “is the best demonstration to date of how machine learning is going to transform medical imaging,” writes Wilson, who blogs independently as The Methods Man.

After running through the researchers’ salient findings, he notes that the study was small, having used slide interpretations from just two sites.

Still, amid all the excitement attending machine learning, “it’s easy to think it’s just a fad. It’s not,” Wilson writes. “Mark my words, studies like this will redefine medical imaging in the near future.”

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