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Using computers to detect breast cancer

Using computers to detect breast cancer


Jeffrey Alan Golden, MD chairman, Department of Pathology, Brigham and Women’s Hospital


Journal of the American Medical Association


Embargoed for release, December 12, 2017 at 11 a.m. ET


“Deep Learning Algorithms for Detection of Lymph Node Metastases from Breast Cancer”

Artificial intelligence, the development of computer systems to perform tasks that typically require humans, is emerging in healthcare. Dr. Golden authored an editorial in JAMA to accompany a new paper, which found that an artificial intelligence application could detect lymph node metastases in breast cancer patients as effectively as pathologists.

“The promise of AI in health care is the delivery of improved quality and safety of care and the potential to democratize expertise,” writes Golden. Golden notes many challenges remain, including an increase in costs due to the technology, training professionals to use these systems, and the need for these applications to prove their benefits in a clinical setting.

“While still requiring evaluation within a normal surgical pathology workflow, deep learning has the opportunity to assist pathologists by improving the efficiency of their work, standardizing quality and providing better prognostication,” writes Golden. While workflow is likely to change, Golden notes the contributions of pathologists in patient care will continue to be critically important.

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Anjali Nimesh

Anjali Nimesh

Anjali Nimesh Joined Medical Dialogue as Reporter in 2016. she covers all the medical specialty news in different medical categories. She also covers the Medical guidelines, Medical Journals, rare medical surgeries as well as all the updates in medical filed. She is a graduate from Dr. Bhimrao Ambedkar University. She can be contacted at Contact no. 011-43720751
Source: Eureka Alert

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