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학술대회 Medication Adherence Supporting Model based on Markov Logic Network using Tuberculosis Patients Data
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저자
김범휘, 권기구, 김규형, 최은창, 나재욱
발행일
201810
출처
International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.66-68
DOI
https://dx.doi.org/10.1109/ICTC.2018.8539524
협약과제
18ZD1100, 대경권 지역산업 기반 ICT융합기술 고도화 지원사업, 문기영
초록
In this paper, we propose a patient medication adherence supporting system to support continuous patient medication for increasing the rate of treatment for tuberculosis. The proposed model is based on the Markov Logic Network which is one of statistical relational learning approach using doctor's decision rule. The Markov logic network learns the relationships of data fields from tuberculosis patients. The proposed model infers medication adherence group using the newly given patient data via the trained Markov logic network.
KSP 제안 키워드
Data field, Decision rules, Learning approach, Markov logic network, Patient data, Proposed model, Statistical relational learning, Supporting system, medication adherence, model-based