NDLI: Predicting health patterns using sensor sequence similarity and NLP

Content Provider	IEEE Xplore Digital Library
Author	Hajihashemi, Z. Popescu, M.
Copyright Year	2012
Description	Author affiliation: Computer Science Department, University of Missouri-Columbia, Columbia, Missouri, USA (Hajihashemi, Z.) \|\| Health Management and Informatics Department University of Missouri-Columbia Columbia, Missouri, USA (Popescu, M.)
Abstract	Health information technology has been used in long-term care to improve outcomes and reduce cost. In Tiger Pace, an aging in place facility from Columbia, MO, we deployed sensor networks together with an electronic health record (EHR) system to provide early illness recognition. In this paper, we describe a methodology for early illness based on non-wearable sensor data and concepts extracted from nursing notes using Natural Language Processing (NLP). The methodology is inspired from genomie sequence annotation using BLAST. First, we extract a set of Unified Medical Language System (UMLS) concepts from each nursing note using Metamap, a NLP tool provided by UMLS. Then, we associate each daily sensor sequence with the medical concepts related to the nursing notes issued that day for that patient. Finally, to infer the health concepts for an unknown day, we compute the similarity between its sensor sequence and those available in the database. The challenges presented by this method are finding the most suitable multi-attribute time sequence similarity and aggregation of the retrieved concepts. On a pilot dataset from three Tiger Place residents, with a total of 1685 sensor days and 358 nursing records, we obtained an average precision of 0.34 and a recall of 0.52.
Starting Page	948
Ending Page	950
File Size	1806385
Page Count	3
File Format	PDF
ISBN	9781467327466
e-ISBN	9781467327473
e-ISBN	9781467327442
DOI	10.1109/BIBMW.2012.6470278
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	health context aware algorithms natural language processing (NLP) Databases Conferences Unified modeling language Medical services Natural language processing Biomedical monitoring Monitoring Eldercare monitoring early illness recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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