Predicting Complications in Critical Care Using Heterogeneous Clinical Data

IEEE Access

Volumn 4, Issue , 2016, Pages 7988-8001

  Huddar, Vijay ^a   Desiraju, Bapu Koundinya ^b   Rajan, Vaibhav ^a   Bhattacharya, Sakyajit ^a   Roy, Shourya ^a   Reddy, Chandan K ^c  

^a Xerox Research Centre   (India)

^b CSIR INSTITUTE OF GENOMICS AND INTEGRATIVE BIOLOGY   (India)

^c VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

Clinical notes; collective matrix factorization; heterogeneous data; multi view learning; postoperative respiratory failure; topic models

Indexed keywords

FACTORIZATION; HOSPITALS; LEARNING SYSTEMS; MEDICAL COMPUTING;

CLINICAL NOTES; COLLECTIVE MATRIX FACTORIZATIONS; HETEROGENEOUS DATA; MULTI-VIEW LEARNING; RESPIRATORY FAILURE; TOPIC MODEL;

MATRIX ALGEBRA;

EID: 85012871270     PISSN: None     EISSN: 21693536     Source Type: Journal    
DOI: 10.1109/ACCESS.2016.2618775     Document Type: Article

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