NDLI: SOM: feature extraction from patient discharge summaries

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SOM: feature extraction from patient discharge summaries

Content Provider	ACM Digital Library
Author	Zincir-Heywood, A. N. Tufts-Conrad, D. J. Zitner, D.
Abstract	In each Canadian province, hospitals collect information, at discharge, on the hospital stay of each patient. The information is collected in the form of a patient discharge abstract (PDA) and sent to the Canadian Institute for Health Information. The Patient Discharge Abstract uses the ICD-10-CA code standard to outline the assigned diagnoses for the patient's condition and the procedures that were performed. One compulsory piece of information in the Patient Discharge Abstract is the identification of the "most responsible diagnosis" (MRDx) -- that diagnosis considered to be the most significant condition of the patient that caused the greatest length of stay in hospital. This research investigates the potential for automating the process of feature extraction from a narrative patient discharge summary to support the classification of the MRDx for a Patient Discharge Abstract. Unsupervised neural networks -- Self-Organizing Maps (SOM) -- are effective for classification tasks based on noisy input patterns. Here a hierarchical architecture of SOMs is used to identify semantic similarities encoded in the original information and visualize the characteristics of an MRDx.
Starting Page	263
Ending Page	267
Page Count	5
File Format	PDF
ISBN	1581136242
DOI	10.1145/952532.952586
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-03-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Health care information Neural networks for medical informatics Computer applications for medical informatics
Content Type	Text
Resource Type	Article

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