Comment on 'Discovering hospital admission patterns using models learnt from electronic hospital records'. the importance of using the right codes

Bioinformatics

Volumn 32, Issue 13, 2016, Pages 2079-2080

  Lopez Campos, Guillermo H ^a   Martin Sanchez, Fernando ^b   Gray, Kathleen ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b WEILL CORNELL MEDICAL COLLEGE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN; MEDICAL RECORD;

HOSPITAL RECORDS; HUMANS;

EID: 85007236164     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btw078     Document Type: Letter

References (4)

1. Arandjelovic,O. (2015a) Discovering hospital admission patterns using models learnt from electronic hospital records. Bioinformatics, 31, 3970-3976.
2. Arandjelovic, O. (2015b) Prediction of health outcomes using big (health) data. Proc. Int. Conf. IEEE Eng. Med. Biol. Soc, 2015, 2543-2546.
3. Cai,X. et al. (2015) Real-time prediction of mortality, readmission, and length of stay using electronic health record data. J. Am. Med. Inf. Assoc., doi:10.1093/jamia/ocv110.
4. McCoy,T.H. et al. (2015) Sentiment Measurement in hospital Discharge Notes is Associated with readmission and mortality risk: an electronic health record study. PLos One, 10. e0136341.