Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records

Abstract The extensive utilization of electronic health records (EHRs) and the growth of enormous open biomedical datasets has readied the area for applications of computational and machine learning techniques to reveal fundamental patterns. This study’s goal is to develop a medical treatment recomm...

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Autores principales:	Sang-Ho Oh, Su Jin Lee, Juhwan Noh, Jeonghoon Mo
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2d3dd63d7cca49b5be668196b3294238
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spelling	oai:doaj.org-article:2d3dd63d7cca49b5be668196b32942382021-12-02T11:45:02ZOptimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records10.1038/s41598-021-86419-42045-2322https://doaj.org/article/2d3dd63d7cca49b5be668196b32942382021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86419-4https://doaj.org/toc/2045-2322Abstract The extensive utilization of electronic health records (EHRs) and the growth of enormous open biomedical datasets has readied the area for applications of computational and machine learning techniques to reveal fundamental patterns. This study’s goal is to develop a medical treatment recommendation system using Korean EHRs along with the Markov decision process (MDP). The sharing of EHRs by the National Health Insurance Sharing Service (NHISS) of Korea has made it possible to analyze Koreans’ medical data which include treatments, prescriptions, and medical check-up. After considering the merits and effectiveness of such data, we analyzed patients’ medical information and recommended optimal pharmaceutical prescriptions for diabetes, which is known to be the most burdensome disease for Koreans. We also proposed an MDP-based treatment recommendation system for diabetic patients to help doctors when prescribing diabetes medications. To build the model, we used the 11-year Korean NHISS database. To overcome the challenge of designing an MDP model, we carefully designed the states, actions, reward functions, and transition probability matrices, which were chosen to balance the tradeoffs between reality and the curse of dimensionality issues.Sang-Ho OhSu Jin LeeJuhwan NohJeonghoon MoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sang-Ho Oh Su Jin Lee Juhwan Noh Jeonghoon Mo Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records
description	Abstract The extensive utilization of electronic health records (EHRs) and the growth of enormous open biomedical datasets has readied the area for applications of computational and machine learning techniques to reveal fundamental patterns. This study’s goal is to develop a medical treatment recommendation system using Korean EHRs along with the Markov decision process (MDP). The sharing of EHRs by the National Health Insurance Sharing Service (NHISS) of Korea has made it possible to analyze Koreans’ medical data which include treatments, prescriptions, and medical check-up. After considering the merits and effectiveness of such data, we analyzed patients’ medical information and recommended optimal pharmaceutical prescriptions for diabetes, which is known to be the most burdensome disease for Koreans. We also proposed an MDP-based treatment recommendation system for diabetic patients to help doctors when prescribing diabetes medications. To build the model, we used the 11-year Korean NHISS database. To overcome the challenge of designing an MDP model, we carefully designed the states, actions, reward functions, and transition probability matrices, which were chosen to balance the tradeoffs between reality and the curse of dimensionality issues.
format	article
author	Sang-Ho Oh Su Jin Lee Juhwan Noh Jeonghoon Mo
author_facet	Sang-Ho Oh Su Jin Lee Juhwan Noh Jeonghoon Mo
author_sort	Sang-Ho Oh
title	Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records
title_short	Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records
title_full	Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records
title_fullStr	Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records
title_full_unstemmed	Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records
title_sort	optimal treatment recommendations for diabetes patients using the markov decision process along with the south korean electronic health records
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/2d3dd63d7cca49b5be668196b3294238
work_keys_str_mv	AT sanghooh optimaltreatmentrecommendationsfordiabetespatientsusingthemarkovdecisionprocessalongwiththesouthkoreanelectronichealthrecords AT sujinlee optimaltreatmentrecommendationsfordiabetespatientsusingthemarkovdecisionprocessalongwiththesouthkoreanelectronichealthrecords AT juhwannoh optimaltreatmentrecommendationsfordiabetespatientsusingthemarkovdecisionprocessalongwiththesouthkoreanelectronichealthrecords AT jeonghoonmo optimaltreatmentrecommendationsfordiabetespatientsusingthemarkovdecisionprocessalongwiththesouthkoreanelectronichealthrecords
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Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records

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