Deep learning approach for survival prediction for patients with synovial sarcoma

Tumor Biology

Volumn 40, Issue 9, 2018, Pages

  Han, Ilkyu ^a   Kim, June Hyuk ^b   Park, Heeseol ^c   Kim, Han Soo ^a   Seo, Sung Wook ^c,d  

^a Seoul National University Hospital   (South Korea)

^b National Cancer Center   (South Korea)

^c Sungkyunkwan University School of Medicine   (South Korea)

^d Sungkyunkwan University   (South Korea)

Author keywords

deep learning; prediction model; survival neural network; Synovial sarcoma

Indexed keywords

ADOLESCENT; ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER PROGNOSIS; CANCER SURVIVAL; CHILD; COMPARATIVE STUDY; DATA ANALYSIS; FEMALE; HUMAN; LEARNING ALGORITHM; MAJOR CLINICAL STUDY; MALE; METASTASIS; PREDICTION; PRIORITY JOURNAL; PROPORTIONAL HAZARDS MODEL; SURVIVAL RATE; SYNOVIAL SARCOMA; VALIDATION PROCESS; ALGORITHM; MIDDLE AGED; PATHOLOGY; PRESCHOOL CHILD; SURVIVAL ANALYSIS; VERY ELDERLY; YOUNG ADULT;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; CHILD; CHILD, PRESCHOOL; FEMALE; HUMANS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); PROPORTIONAL HAZARDS MODELS; SARCOMA, SYNOVIAL; SURVIVAL ANALYSIS; YOUNG ADULT;

EID: 85054141684     PISSN: 10104283     EISSN: 14230380     Source Type: Journal    
DOI: 10.1177/1010428318799264     Document Type: Article

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