loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Keisuke Ogawa 1 ; Kazunori Matsumoto 1 ; Masayuki Hashimoto 1 and Ryoichi Nagatomi 2

Affiliations: 1 KDDI R&D Labs, Japan ; 2 Tohoku Graduate School of Biomedical Engineering, Japan

ISBN: 978-989-758-068-0

Keyword(s): Latent Dirichlet Allocation, LDA, Metabolic Syndrome, Lifestyle-Related Disease.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cloud Computing ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; e-Health ; Enterprise Information Systems ; Health Information Systems ; Pattern Recognition and Machine Learning ; Platforms and Applications ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Recently, the number of patients with lifestyle-related diseases, such as diabetes mellitus, has increased dramatically. Lifestyle-related diseases are responsible for 60% of deaths in Japan. In order to screen persons at potentially high risk for these diseases, medical checkups for metabolic syndrome are used throughout Japan. Prediction and prevention of lifestyle-related diseases would yield a direct reduction in medical costs. However, many cases cannot be screened with a metabolic syndrome checkup. In this paper, we propose a new machine-learning-based screening method using medical checkup data and medical billings. By processing the medical data into a bag-of-words representation and classifying the health factors using latent Dirichlet allocation (LDA), the screening method achieves high accuracy. We evaluate the method by comparing the accuracy of predictions of the future incidence of the diseases. The results show that F-measure increases 0.17 compared with the conventiona l method. In addition, we confirmed that the proposed method classified persons with different health risk factors, such as a combination of metabolic disorders, hypertensive disorders, and mental disorders (stress). (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.214.184.124

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ogawa, K.; Matsumoto, K.; Hashimoto, M. and Nagatomi, R. (2015). Method of Screening the Health of Persons with High Risk for Potential Lifestyle-related Diseases using LDA - Toward a Better Screening Method for Persons with High Health Risks.In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015) ISBN 978-989-758-068-0, pages 502-507. DOI: 10.5220/0005250905020507

@conference{healthinf15,
author={Keisuke Ogawa. and Kazunori Matsumoto. and Masayuki Hashimoto. and Ryoichi Nagatomi.},
title={Method of Screening the Health of Persons with High Risk for Potential Lifestyle-related Diseases using LDA - Toward a Better Screening Method for Persons with High Health Risks},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)},
year={2015},
pages={502-507},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005250905020507},
isbn={978-989-758-068-0},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)
TI - Method of Screening the Health of Persons with High Risk for Potential Lifestyle-related Diseases using LDA - Toward a Better Screening Method for Persons with High Health Risks
SN - 978-989-758-068-0
AU - Ogawa, K.
AU - Matsumoto, K.
AU - Hashimoto, M.
AU - Nagatomi, R.
PY - 2015
SP - 502
EP - 507
DO - 10.5220/0005250905020507

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.