AI may help radiologists reduce missed breast cancer cases

(Matt O’Connor / HealthImaging) — A combined deep and machine learning approach trained to read mammograms and electronic health records (EHRs) may be used to greatly reduce missed breast cancer cases, according to a June 18 study published in Radiology.

The algorithm, trained on more than 9,000 mammograms and EHRs, predicted breast malignancy within one year of the index examination with 87% sensitivity, said Ayelet Akselrod-Ballin, PhD, with IBM Research’s Department of Healthcare Informatics, University of Haifa Campus in Israel, and colleagues.

“In a scenario where double reading at screening mammography is not available…we believe that the use of this model as a second reader could be beneficial,” Akselrod-Ballin et al. added. Such a model may even be used to recommend an individual breast cancer screening plan, the group noted. (…)

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