DeepHit: A deep learning approach to survival analysis with competing risks

32nd AAAI Conference on Artificial Intelligence, AAAI 2018

Volumn , Issue , 2018, Pages 2314-2321

  Lee, Changhee ^a   Zame, William R ^b   Yoon, Jinsung ^a   Van Der Schaar, Mihaela ^a,c,d  

^a Department of Civil and Environmental Engineering   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF OXFORD   (United Kingdom)

^d ALAN TURING INSTITUTE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; DEEP NEURAL NETWORKS; RANDOM PROCESSES; RISK PERCEPTION; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

COMPETING RISKS; FIRST HITTING TIME; LEARNING APPROACH; PERFORMANCE IMPROVEMENTS; STATE-OF-THE-ART METHODS; SURVIVAL ANALYSIS; SYNTHETIC DATASETS; TIME TO EVENTS;

RISK ASSESSMENT;

EID: 85060469637     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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