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An Inference Engine for Estimating Outside States of Clinical Test Items

An Inference Engine for Estimating Outside States of Clinical Test Items An Inference Engine for Estimating Outside States of Clinical Test Items ¨ MASATO SAKATA, ZEYNEP YUCEL, KAZUHIKO SHINOZAWA, and NORIHIRO HAGITA, Advanced Telecommunications Research Institute MICHITA IMAI, Advanced Telecommunications Research Institute and Keio University MICHIKO FURUTANI, Tokyo Women's Medical University RUMIKO MATSUOKA, Tokyo Women's Medical University and Toho University Common periodical health check-ups include several clinical test items with affordable cost. However, these standard tests do not directly indicate signs of most lifestyle diseases. In order to detect such diseases, a number of additional specific clinical tests are required, which increase the cost of the health check-up. This study aims to enrich our understanding of the common health check-ups and proposes a way to estimate the signs of several lifestyle diseases based on the standard tests in common examinations without performing any additional specific tests. In this manner, we enable a diagnostic process, where the physician may prefer to perform or avoid a costly test according to the estimation carried out through a set of common affordable tests. To that end, the relation between standard and specific test results is modeled with a multivariate kernel density estimate. The condition of the patient regarding a specific test is assessed http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Management Information Systems (TMIS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2013 by ACM Inc.
ISSN
2158-656X
DOI
10.1145/2517084
Publisher site
See Article on Publisher Site

Abstract

An Inference Engine for Estimating Outside States of Clinical Test Items ¨ MASATO SAKATA, ZEYNEP YUCEL, KAZUHIKO SHINOZAWA, and NORIHIRO HAGITA, Advanced Telecommunications Research Institute MICHITA IMAI, Advanced Telecommunications Research Institute and Keio University MICHIKO FURUTANI, Tokyo Women's Medical University RUMIKO MATSUOKA, Tokyo Women's Medical University and Toho University Common periodical health check-ups include several clinical test items with affordable cost. However, these standard tests do not directly indicate signs of most lifestyle diseases. In order to detect such diseases, a number of additional specific clinical tests are required, which increase the cost of the health check-up. This study aims to enrich our understanding of the common health check-ups and proposes a way to estimate the signs of several lifestyle diseases based on the standard tests in common examinations without performing any additional specific tests. In this manner, we enable a diagnostic process, where the physician may prefer to perform or avoid a costly test according to the estimation carried out through a set of common affordable tests. To that end, the relation between standard and specific test results is modeled with a multivariate kernel density estimate. The condition of the patient regarding a specific test is assessed

Journal

ACM Transactions on Management Information Systems (TMIS)Association for Computing Machinery

Published: Oct 1, 2013

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