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008181129s2018 ||| | | | eng d
020 ▼a 9780438126091
035 ▼a (MiAaPQ)AAI10903003
035 ▼a (MiAaPQ)umichrackham:001241
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 658
1001 ▼a Merdan, Selin.
24510 ▼a Optimization and Machine Learning Methods for Diagnostic Testing of Prostate Cancer.
260 ▼a [S.l.] : ▼b University of Michigan., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 155 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Brian Denton.
5021 ▼a Thesis (Ph.D.)--University of Michigan, 2018.
520 ▼a Technological advances in biomarkers and imaging tests are creating new avenues to advance precision health for early detection of cancer. These advances have resulted in multiple layers of information that can be used to make clinical decisions
520 ▼a In the first part, we develop and validate predictive models to assess individual PCa risk using known clinical risk factors. Because not all men with newly-diagnosed PCa received imaging at diagnosis, we use an established method to correct for
520 ▼a In the second part of this thesis, we combine optimization and machine learning approaches into a robust optimization framework to design imaging guidelines that can account for imperfect calibration of predictions. We investigate efficient and
520 ▼a In the third and final part of this thesis, we investigate the optimal design of composite multi-biomarker tests to achieve early detection of prostate cancer. Biomarker tests vary significantly in cost, and cause false positive and false negati
520 ▼a In this dissertation, we identify new principles and methods to guide the design of early detection protocols for PCa using new diagnostic technologies. We provide important clinical evidence that can be used to improve health outcomes of patien
590 ▼a School code: 0127.
650 4 ▼a Industrial engineering.
690 ▼a 0546
71020 ▼a University of Michigan. ▼b Industrial & Operations Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0127
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000511 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자