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Decision analytics and optimization in disease prevention and treatment / edited by Nan Kong, Shengfan Zhang.

Contributor(s): Material type: TextSeries: Wiley series in operations research and management sciencePublisher: Hoboken, NJ : Wiley, 2018Copyright date: �2018Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118960141
  • 1118960149
  • 9781118960158
  • 1118960157
Subject(s): Additional physical formats: Print version:: Decision analytics and optimization in disease prevention and treatment.DDC classification:
  • 616.9 23
LOC classification:
  • RA643
NLM classification:
  • WA 108
Online resources:
Contents:
Optimization in infectious disease control and prevention : tuberculosis modeling using microsimulation / Sze-chuan Suen -- Saving lives with operations research : models to improve HIV resource allocation / Sabina S. Alistar, Margaret L. Brandeau -- Adaptive decision making during epidemics / Reza Yaesoubi, Ted Cohen -- Assessing register-based chlamydia infection screening programs : a cost-effectiveness analysis on screening start/end age and frequency / Yu Teng, Nan Kong, Wanzhu Tu -- Optimal selection of assays for detecting infectious agents in donated blood / Ebru K. Bish, Hadi El-Amine, Douglas R. Bish, Susan L. Stramer, Anthony D. Slonim -- Modeling chronic hepatitis C during rapid therapeutic advance : cost-effective screening, monitoring and treatment strategies / Shan Liu -- Modeling disease progression and risk-differentiated screening for cervical cancer prevention / Adriana Ley-Chavez, Julia L. Higle -- Using finite-horizon Markov decision processes for optimizing post-mammography diagnostic decisions / Sait Tunc, Oguzhan Alagoz, Jagpreet Chhatwal, Elizabeth S. Burside -- Partially observable Markov decision processes for prostate cancer screening, surveillance, and treatment : a budgeted sampling approximation method / Jingyu Zhang, Brian T. Denton -- Cost-effectiveness analysis of breast cancer mammography screening policies considering heterogeneity in women's adherence / Mahboubeh Madadi, Shengfan Zhang -- An agent-based model for ideal cardiovascular health / Yan Li, Nan Kong, Mark A. Lawley, Jose A. Pag�an -- Biological planning optimization for high-dose-rate brachytherapy and its application to cervical cancer treatment / Eva K. Lee, Fan Yuan, Alistair Templeton, Rui Yao, Krystyna Kiel, James CH Chu -- Fluence map optimization in intensity modulated radiation therapy treatment planning / Dionne M. Aleman -- Sliding window IMRT and VMAT optimization / David Craft, Taret Hlibi -- Modeling the cardiovascular disease prevention-treatment tradeoff / George Miller -- Treatment optimization for patients with type 2 diabetes / Jennifer Mason Lobo -- Machine learning for early detection and treatment outcome prediction / Eva K. Lee.
Summary: A systematic review of the most current decision models and techniques for disease prevention and treatment Decision Analytics and Optimization in Disease Prevention and Treatment offers a comprehensive resource of the most current decision models and techniques for disease prevention and treatment. With contributions from leading experts in the field, this important resource presents information on the optimization of chronic disease prevention, infectious disease control and prevention, and disease treatment and treatment technology. Designed to be accessible, in each chapter the text presents one decision problem with the related methodology to showcase the vast applicability of operations research tools and techniques in advancing medical decision making. This vital resource features the most recent and effective approaches to the quickly growing field of healthcare decision analytics, which involves cost-effectiveness analysis, stochastic modeling, and computer simulation. Throughout the book, the contributors discuss clinical applications of modeling and optimization techniques to assist medical decision making within complex environments. Accessible and authoritative, Decision Analytics and Optimization in Disease Prevention and Treatment: -Presents summaries of the state-of-the-art research that has successfully utilized both decision analytics and optimization tools within healthcare operations research -Highlights the optimization of chronic disease prevention, infectious disease control and prevention, and disease treatment and treatment technology -Includes contributions by well-known experts from operations researchers to clinical researchers, and from data scientists to public health administrators -Offers clarification on common misunderstandings and misnomers while shedding light on new approaches in this growing area Designed for use by academics, practitioners, and researchers, Decision Analytics and Optimization in Disease Prevention and Treatment offers a comprehensive resource for accessing the power of decision analytics and optimization tools within healthcare operations research.
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Includes bibliographical references and index.

Optimization in infectious disease control and prevention : tuberculosis modeling using microsimulation / Sze-chuan Suen -- Saving lives with operations research : models to improve HIV resource allocation / Sabina S. Alistar, Margaret L. Brandeau -- Adaptive decision making during epidemics / Reza Yaesoubi, Ted Cohen -- Assessing register-based chlamydia infection screening programs : a cost-effectiveness analysis on screening start/end age and frequency / Yu Teng, Nan Kong, Wanzhu Tu -- Optimal selection of assays for detecting infectious agents in donated blood / Ebru K. Bish, Hadi El-Amine, Douglas R. Bish, Susan L. Stramer, Anthony D. Slonim -- Modeling chronic hepatitis C during rapid therapeutic advance : cost-effective screening, monitoring and treatment strategies / Shan Liu -- Modeling disease progression and risk-differentiated screening for cervical cancer prevention / Adriana Ley-Chavez, Julia L. Higle -- Using finite-horizon Markov decision processes for optimizing post-mammography diagnostic decisions / Sait Tunc, Oguzhan Alagoz, Jagpreet Chhatwal, Elizabeth S. Burside -- Partially observable Markov decision processes for prostate cancer screening, surveillance, and treatment : a budgeted sampling approximation method / Jingyu Zhang, Brian T. Denton -- Cost-effectiveness analysis of breast cancer mammography screening policies considering heterogeneity in women's adherence / Mahboubeh Madadi, Shengfan Zhang -- An agent-based model for ideal cardiovascular health / Yan Li, Nan Kong, Mark A. Lawley, Jose A. Pag�an -- Biological planning optimization for high-dose-rate brachytherapy and its application to cervical cancer treatment / Eva K. Lee, Fan Yuan, Alistair Templeton, Rui Yao, Krystyna Kiel, James CH Chu -- Fluence map optimization in intensity modulated radiation therapy treatment planning / Dionne M. Aleman -- Sliding window IMRT and VMAT optimization / David Craft, Taret Hlibi -- Modeling the cardiovascular disease prevention-treatment tradeoff / George Miller -- Treatment optimization for patients with type 2 diabetes / Jennifer Mason Lobo -- Machine learning for early detection and treatment outcome prediction / Eva K. Lee.

Print version record and CIP data provided by publisher; resource not viewed.

A systematic review of the most current decision models and techniques for disease prevention and treatment Decision Analytics and Optimization in Disease Prevention and Treatment offers a comprehensive resource of the most current decision models and techniques for disease prevention and treatment. With contributions from leading experts in the field, this important resource presents information on the optimization of chronic disease prevention, infectious disease control and prevention, and disease treatment and treatment technology. Designed to be accessible, in each chapter the text presents one decision problem with the related methodology to showcase the vast applicability of operations research tools and techniques in advancing medical decision making. This vital resource features the most recent and effective approaches to the quickly growing field of healthcare decision analytics, which involves cost-effectiveness analysis, stochastic modeling, and computer simulation. Throughout the book, the contributors discuss clinical applications of modeling and optimization techniques to assist medical decision making within complex environments. Accessible and authoritative, Decision Analytics and Optimization in Disease Prevention and Treatment: -Presents summaries of the state-of-the-art research that has successfully utilized both decision analytics and optimization tools within healthcare operations research -Highlights the optimization of chronic disease prevention, infectious disease control and prevention, and disease treatment and treatment technology -Includes contributions by well-known experts from operations researchers to clinical researchers, and from data scientists to public health administrators -Offers clarification on common misunderstandings and misnomers while shedding light on new approaches in this growing area Designed for use by academics, practitioners, and researchers, Decision Analytics and Optimization in Disease Prevention and Treatment offers a comprehensive resource for accessing the power of decision analytics and optimization tools within healthcare operations research.

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