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Authors: Masatoshi Nagata ; Kazunori Matsumoto and Masayuki Hashimoto

Affiliation: KDDI R&D Labs, Japan

ISBN: 978-989-758-170-0

ISSN: 2184-4305

Keyword(s): Sequential Latent Dirichlet Allocation, LDA, Sequential LDA, Lifestyle-related Disease, Medical Cost.

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

Abstract: Foreseeing the medical expenditure is beneficial for both insurance companies and individuals. In this paper we propose a new methodology to predict disease risk and medical cost. Based on sequential latent dirichlet allocation (SeqLDA), which classifies hierarchical sequential data into segments of topics, we tried to predict the number of people with diseases and the one-year cost of lifestyle-related diseases. Using the health checkup information and medical claims of 6500 people for three years, we achieved that prediction error was less than conventional LDA, and for accuracy rate, AUC was more than 0.71. The results suggest that the SeqLDA method serve to predict the number of people with diseases and the related medical costs using time series healthcare data.

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Paper citation in several formats:
Nagata, M.; Matsumoto, K. and Hashimoto, M. (2016). Prediction for Disease Risk and Medical Cost using Time Series Healthcare Data.In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5 HEALTHINF: HEALTHINF, (BIOSTEC 2016) ISBN 978-989-758-170-0, ISSN 2184-4305, pages 517-522. DOI: 10.5220/0005827405170522

@conference{healthinf16,
author={Masatoshi Nagata. and Kazunori Matsumoto. and Masayuki Hashimoto.},
title={Prediction for Disease Risk and Medical Cost using Time Series Healthcare Data},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5 HEALTHINF: HEALTHINF, (BIOSTEC 2016)},
year={2016},
pages={517-522},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005827405170522},
isbn={978-989-758-170-0},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5 HEALTHINF: HEALTHINF, (BIOSTEC 2016)
TI - Prediction for Disease Risk and Medical Cost using Time Series Healthcare Data
SN - 978-989-758-170-0
AU - Nagata, M.
AU - Matsumoto, K.
AU - Hashimoto, M.
PY - 2016
SP - 517
EP - 522
DO - 10.5220/0005827405170522

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