Data driven studies on the efficacy of healthcare applications and strategies for improving user compliance with these applications = 헬스케어 어플리케이션의 효용성 검증 및 사용 증진 전략에 관한 데이터 기반 연구

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With the recent interest in wellness, the use of various smartphone healthcare applications has grown rapidly. However, there is a lack of research on the efficacy of healthcare applications and strategies for improving user compliance with these applications. This thesis has conducted research on the efficacy and promotion strategies of smartphone healthcare applications through three studies. In the first study, I examined whether mood logs collected through emoticon questionnaires through smartphone application is effective for depression screening. In the second study, it was proved that the accuracy of depression screening could be improved by applying high quality data filtered by machine learning methods. In the third study, I verified whether the promotional effect offered by a firm to the customer is effective in improving application retention.
Advisors
Lee, Byungtaeresearcher이병태researcher
Description
한국과학기술원 :경영공학부,
Publisher
한국과학기술원
Issue Date
2018
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 경영공학부, 2018.2,[x, 91 p. :]

Keywords

Machine learning▼ahealthcare applications▼auser compliance (adherence)▼adepression▼amobile marketing; 기계학습▼a건강관리 어플리케이션▼a고객 순응도▼a우울증; 모바일 마케팅

URI
http://hdl.handle.net/10203/264443
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=842558&flag=dissertation
Appears in Collection
MT-Theses_Ph.D.(박사논문)
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