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Conference Paper
Algorithm and System for Improving the Medication Adherence of Tuberculosis Patients
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- Authors
- Kyuhyung Kim, Bumhwi Kim, Albert Jin Chung, Keekoo Kwon, Eunchang Choi, Jae-wook Nah
- Issue Date
- 2018-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.914-916
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Tuberculosis (TB) is one of the top 10 causes of death in the world and is a major health threat in the developing countries. There are two ways to reduce death from tuberculosis. One is rapid and accurate diagnosis and the other is DOTS (Directly observed treatment, short-course), which is the tuberculosis (TB) control strategy recommended by the World Health Organization. In this paper, we propose the AI algorithm for the effective management of the tuberculosis patient by using DOTS. For this purpose, we used the patient's real time medication data. Additionally, we divided two phased for the prediction of medication adherence, one is the screening phase and the other is the medication monitoring phase. We think that is a way to reduce the overall cost of treating tuberculosis patients.
- KSP Keywords
- Control strategy, Developing Countries, Effective management, Real-Time, medication adherence