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Machine Learning for Data-driven Biomedical Decision Making
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Luckett, Daniel J. |
| 단체저자명 | The University of North Carolina at Chapel Hill. Biostatistics. |
| 서명/저자사항 | Machine Learning for Data-driven Biomedical Decision Making. |
| 발행사항 | [S.l.] : The University of North Carolina at Chapel Hill., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 152 p. |
| 소장본 주기 | School code: 0153. |
| ISBN | 9780438063235 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Michael R. Kosorok. |
| 요약 | The big data age has brought with it challenges and opportunities for biomedical decision making. New technologies allow for collecting large data sets that can be used to tailor treatment. In this dissertation, we develop machine learning metho |
| 요약 | Many problems in biomedical decision making can be expressed as classification problems. The costs of false positives and false negatives differ across application domains and this trade-off is often displayed using a receiver operating characte |
| 요약 | Precision medicine is the paradigm of incorporating individual patient factors into treatment decisions, formalized through individualized treatment regimes (ITR's), or maps from the covariate space into the treatment space. The optimal ITR is d |
| 요약 | Clinical decision making often requires balancing trade-offs between multiple outcomes while accounting for patient preferences, creating a disconnect with the traditional definition of the optimal ITR. If an instrument to elicit patient prefere |
| 요약 | Direct search methods, such as outcome weighted learning (OWL), estimate the optimal ITR by maximizing an inverse probability weighted estimator (IPWE) over a class of ITR's. In the final chapter, we show that the IPWE objective function is a pr |
| 일반주제명 | Biostatistics. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-10B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14997419 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00026838 | 574 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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