PubMed-supported clinical term weighting approach for improving inter-patient similarity measure in diagnosis prediction - Citegraph

Paper Info

Title
PubMed-supported clinical term weighting approach for improving inter-patient similarity measure in diagnosis prediction

Abstract
Similarity-based retrieval of Electronic Health Records (EHRs) from large clinical information systems provides physicians the evidence support in making diagnoses or referring examinations for the suspected cases. Clinical Terms in EHRs represent high-level conceptual information and the similarity measure established based on these terms reflects the chance of inter-patient disease co-occurrence. The assumption that clinical terms are equally relevant to a disease is unrealistic, reducing the prediction accuracy. Here we propose a term weighting approach supported by PubMed search engine to address this issue.

Year	DOI	Venue
2015	10.1186/s12911-015-0166-2	BMC Med. Inf. & Decision Making
Keywords	Field	DocType
Feature Vector, Conditional Probability, Similarity Score, Receiver Operating Characteristic, Electronic Health Record	Data mining,Feature vector,Weighting,Receiver operating characteristic,Similarity measure,Conditional probability,Computer science,Health informatics,Statistics,Direction cosine,Medical diagnosis	Journal
Volume	Issue	ISSN
15	1	1472-6947
Citations	PageRank	References
2	0.39	11
Authors
12

Authors (12 rows)

Cited by (2 rows)

References (11 rows)

Name	Order	Citations	PageRank
Lawrence Wing-Chi Chan	1	8	1.85
Ying Liu	2	1417	91.19
Tao Chan	3	3	0.78
Helen K. W. Law	4	2	0.73
S. C. Wong	5	2	0.39
Andy Yeung	6	2	0.39
K. F. Lo	7	2	0.39
S. W. Yeung	8	2	0.39
Kwok-Yung Yuen	9	30	1.61
William Chan	10	357	24.67
Thomas Lau	11	2	0.39
Chi-Ren Shyu	12	656	67.58

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