Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

Nature Medicine

Volumn 24, Issue 10, 2018, Pages 1559-1567

  Coudray, Nicolas ^a   Ocampo, Paolo Santiago ^a   Sakellaropoulos, Theodore ^b   Narula, Navneet ^a   Snuderl, Matija ^a   Fenyö, David ^a   Moreira, Andre L ^a,c   Razavian, Narges ^a   Tsirigos, Aristotelis ^a  

^a NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^c NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EPIDERMAL GROWTH FACTOR RECEPTOR; K RAS PROTEIN; PROTEIN KINASE LKB1; PROTEIN P53; TUMOR PROTEIN;

AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOANALYSIS; CANCER CLASSIFICATION; CANCER DIAGNOSIS; COMPARATIVE STUDY; CONTROLLED STUDY; GENE FREQUENCY; GENE MUTATION; HISTOPATHOLOGY; HUMAN; LEARNING; LUNG ADENOCARCINOMA; LUNG BIOPSY; LUNG PARENCHYMA; NON SMALL CELL LUNG CANCER; PATHOLOGIST; PREDICTION; PRIORITY JOURNAL; SQUAMOUS CELL LUNG CARCINOMA; ADENOCARCINOMA; CLASSIFICATION; GENE EXPRESSION REGULATION; GENETICS; MUTATION; PATHOLOGY; SQUAMOUS CELL CARCINOMA;

ADENOCARCINOMA; CARCINOMA, NON-SMALL-CELL LUNG; CARCINOMA, SQUAMOUS CELL; DEEP LEARNING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; MUTATION; NEOPLASM PROTEINS; NEURAL NETWORKS (COMPUTER);

EID: 85053661755     PISSN: 10788956     EISSN: 1546170X     Source Type: Journal    
DOI: 10.1038/s41591-018-0177-5     Document Type: Article

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