NDLI: Automated risk assessment tool for pregnancy care

Content Provider	IEEE Xplore Digital Library
Author	Gorthi, A. Firtion, C. Vepa, J.
Copyright Year	2009
Description	Author affiliation: Philips Research Asia-Bangalore, Bangalore, India 560045 (Gorthi, A.; Firtion, C.; Vepa, J.)
Abstract	Clinical decision support systems augment the quality of medical care by aiding healthcare workers in the evaluation and management of complicated cases. Clinical decision support systems are especially instrumental in quickly assessing the criticality of pregnancy as it involves interpreting multiple maternal and fetal parameters. We propose a machine learning approach for early determination of the risk category of pregnancy based on patterns gleaned from profiles of known clinical parameters. In particular, we demonstrate the usefulness of classification and regression trees in solving multivariate problems in obstetric care since the decision making process and the importance of specific parameters are clearly illustrated in the tree. As proof of concept, an application use case has been presented.
Starting Page	6222
Ending Page	6225
File Size	649038
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5334644
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Risk management Pregnancy Decision support systems Medical services Quality management Instruments Machine learning Classification tree analysis Regression tree analysis Decision making Clinical Decision Support System (CDSS) Pregnancy Risk Assessment decision tree-based learning
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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