Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer

American Journal of Surgical Pathology

Volumn 42, Issue 12, 2018, Pages 1636-1646

  Steiner, David F ^a   Macdonald, Robert ^a   Liu, Yun ^a   Truszkowski, Peter ^a   Hipp, Jason D ^a   Gammage, Christopher ^a   Thng, Florence ^b   Peng, Lily ^a   Stumpe, Martin C ^a  

^a GOOGLE INC   (United States)

^b VERILY LIFE SCIENCES   (United States)

Author keywords

artificial intelligence; breast cancer; computer aided detection; digital pathology; machine learning

Indexed keywords

AUTOMATED PATTERN RECOGNITION; BIOPSY; BREAST TUMOR; COMPUTER ASSISTED DIAGNOSIS; EVALUATION STUDY; FEMALE; HUMAN; LYMPH NODE; LYMPH NODE METASTASIS; MICROMETASTASIS; OBSERVER VARIATION; PATHOLOGY; PREDICTIVE VALUE; PROCEDURES; PROOF OF CONCEPT; REPRODUCIBILITY; TIME FACTOR; WORKFLOW;

BIOPSY; BREAST NEOPLASMS; DEEP LEARNING; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LYMPH NODES; LYMPHATIC METASTASIS; NEOPLASM MICROMETASTASIS; OBSERVER VARIATION; PATHOLOGY, CLINICAL; PATTERN RECOGNITION, AUTOMATED; PREDICTIVE VALUE OF TESTS; PROOF OF CONCEPT STUDY; REPRODUCIBILITY OF RESULTS; TIME FACTORS; WORKFLOW;

EID: 85056358333     PISSN: 01475185     EISSN: 15320979     Source Type: Journal    
DOI: 10.1097/PAS.0000000000001151     Document Type: Article

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