A framework for mining signatures from event sequences and its applications in healthcare data

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 2, 2013, Pages 272-285

  Wang, Fei ^a   Lee, Noah ^b   Hu, Jianying ^a   Sun, Jimeng ^a   Ebadollahi, Shahram ^a   Laine, Andrew F ^c  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b 1010data ^*  (United States)

^c Columbia University ^*  (United States)

Author keywords

beta divergence; dictionary learning; nonnegative matrix factorization; sparse coding; stochastic gradient descent; Temporal signature mining

Indexed keywords

BETA-DIVERGENCE; DICTIONARY LEARNING; NONNEGATIVE MATRIX FACTORIZATION; SPARSE CODING; STOCHASTIC GRADIENT DESCENT; TEMPORAL SIGNATURES;

HEALTH CARE; KNOWLEDGE REPRESENTATION;

GRAPHICAL USER INTERFACES;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; DATA BASE; DATA MINING; DECISION SUPPORT SYSTEM; ELECTRONIC MEDICAL RECORD; MEDICAL RECORD; METHODOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA MINING; DATABASE MANAGEMENT SYSTEMS; DECISION SUPPORT SYSTEMS, CLINICAL; DECISION SUPPORT TECHNIQUES; ELECTRONIC HEALTH RECORDS; HEALTH RECORDS, PERSONAL; PATTERN RECOGNITION, AUTOMATED;

MLCS; MLOWN;

EID: 84871741964     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.111     Document Type: Article

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