Prediction and factor extraction of drug function by analyzing medical records in developing countries

Min Hu, Yasunobu Nohara, Masafumi Nakamura, Naoki Nakashima

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict pharmaceutical prescriptions may solve HRH crises. In this study, we investigate a predictive model by analyzing prescription data of 4,543 subjects in Bangladesh. We predict the function of prescribed drugs, comparing three machine-learning approaches. The approaches compare whether a subject shall be prescribed medicine from the 21 most frequently prescribed drug functions. Receiver Operating Characteristics (ROC) were selected as a way to evaluate and assess prediction models. The results show the drug function with the best prediction performance was oral hypoglycemic drugs, which has an average AUC of 0.962. To understand how the variables affect prediction, we conducted factor analysis based on tree-based algorithms and natural language processing techniques.

Original languageEnglish
Title of host publicationMEDINFO 2017
Subtitle of host publicationPrecision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics
EditorsZhao Dongsheng, Adi V. Gundlapalli, Jaulent Marie-Christine
PublisherIOS Press
Pages403-407
Number of pages5
ISBN (Electronic)9781614998297
DOIs
Publication statusPublished - Jan 1 2017
Event16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, China
Duration: Aug 21 2017Aug 25 2017

Publication series

NameStudies in Health Technology and Informatics
Volume245
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
CountryChina
CityHangzhou
Period8/21/178/25/17

Fingerprint

Developing countries
Developing Countries
Medical Records
Health
Bangladesh
Learning systems
Health Resources
Personnel
Pharmaceutical Preparations
Prescriptions
Trees (mathematics)
Natural Language Processing
Factor analysis
Drug products
Artificial intelligence
Artificial Intelligence
Hypoglycemic Agents
ROC Curve
Statistical Factor Analysis
Area Under Curve

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Hu, M., Nohara, Y., Nakamura, M., & Nakashima, N. (2017). Prediction and factor extraction of drug function by analyzing medical records in developing countries. In Z. Dongsheng, A. V. Gundlapalli, & J. Marie-Christine (Eds.), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics (pp. 403-407). (Studies in Health Technology and Informatics; Vol. 245). IOS Press. https://doi.org/10.3233/978-1-61499-830-3-403

Prediction and factor extraction of drug function by analyzing medical records in developing countries. / Hu, Min; Nohara, Yasunobu; Nakamura, Masafumi; Nakashima, Naoki.

MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. ed. / Zhao Dongsheng; Adi V. Gundlapalli; Jaulent Marie-Christine. IOS Press, 2017. p. 403-407 (Studies in Health Technology and Informatics; Vol. 245).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hu, M, Nohara, Y, Nakamura, M & Nakashima, N 2017, Prediction and factor extraction of drug function by analyzing medical records in developing countries. in Z Dongsheng, AV Gundlapalli & J Marie-Christine (eds), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 245, IOS Press, pp. 403-407, 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017, Hangzhou, China, 8/21/17. https://doi.org/10.3233/978-1-61499-830-3-403
Hu M, Nohara Y, Nakamura M, Nakashima N. Prediction and factor extraction of drug function by analyzing medical records in developing countries. In Dongsheng Z, Gundlapalli AV, Marie-Christine J, editors, MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. IOS Press. 2017. p. 403-407. (Studies in Health Technology and Informatics). https://doi.org/10.3233/978-1-61499-830-3-403
Hu, Min ; Nohara, Yasunobu ; Nakamura, Masafumi ; Nakashima, Naoki. / Prediction and factor extraction of drug function by analyzing medical records in developing countries. MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. editor / Zhao Dongsheng ; Adi V. Gundlapalli ; Jaulent Marie-Christine. IOS Press, 2017. pp. 403-407 (Studies in Health Technology and Informatics).
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