A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	596-600
Journal	Journal of the American Medical Informatics Association
Volume	16
Issue number	4
DOIs	https://doi.org/10.1197/jamia.m3096
Publication status	Published - 1 Jul 2009

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title = "A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries",

author = "H. Yang and I. Spasic and Keane, \{J. A.\} and G. Nenadic",

year = "2009",

month = jul,

day = "1",

doi = "10.1197/jamia.m3096",

language = "English",

volume = "16",

pages = "596--600",

journal = "Journal of the American Medical Informatics Association",

issn = "1067-5027",

publisher = "Oxford University Press",

number = "4",

}

TY - JOUR

T1 - A Text Mining Approach to the Prediction of Disease Status from Clinical Discharge Summaries

AU - Yang, H.

AU - Spasic, I.

AU - Keane, J. A.

AU - Nenadic, G.

PY - 2009/7/1

Y1 - 2009/7/1

U2 - 10.1197/jamia.m3096

DO - 10.1197/jamia.m3096

M3 - Article

SN - 1067-5027

VL - 16

SP - 596

EP - 600

JO - Journal of the American Medical Informatics Association

JF - Journal of the American Medical Informatics Association

IS - 4

ER -