From Pharmaphorum News: AI Outperforms Experts in Breast Cancer Diagnosis

| December 20, 2017

More headlines and news about man versus machine. I think in the end what will be used is a combination of the two – that will improve pathologist efficiency but is still required to supervise these algorithms.

Artificial intelligence outperformed a panel of experts in a simulation where they were asked to diagnose breast cancer based on stained tissue samples – suggesting deep learning algorithms could be used to help clinicians diagnose cancer in the clinic.

study published in the Journal of the American Medical Association opens the door for further research into AI and its ability to improve diagnosis.

The study was based on an analysis of a training data set of whole-slide images from two centres from the Netherlands – 110 with and 160 without verified nodal metastases.

It tested the performance of seven deep learning algorithms against a panel of 11 pathologists with time constraint to simulate the real clinical environment, and one pathologist without time constraint. The best-performing algorithm’s performance was comparable with the pathologist without time constraint, at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task the best algorithm performed significantly better than the time-limited pathologists.

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Category: Artificial Intelligence, Clinical Laboratories, Clinical Pathology, Data Management, Digital Pathology News, Electronic Medical Records, File format, Image Analysis, Informatics, Laboratory Informatics, Laboratory Information Systems, Laboratory Management & Operations, New Digital Imaging Technologies, Pathology News, Standards and Guidelines, Vendor products, Web/Tech, Whole slide

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