K H Benjamin Leung, Nasrin Yousefi, Timothy C Y Chan, Ahmed M Bayoumi
{"title":"Constrained Optimization for Decision Making in Health Care Using Python: A Tutorial.","authors":"K H Benjamin Leung, Nasrin Yousefi, Timothy C Y Chan, Ahmed M Bayoumi","doi":"10.1177/0272989X231188027","DOIUrl":null,"url":null,"abstract":"<p><strong>Highlights: </strong>This tutorial provides a user-friendly guide to mathematically formulating constrained optimization problems and implementing them using Python.Two examples are presented to illustrate how constrained optimization is used in health applications, with accompanying Python code provided.</p>","PeriodicalId":49839,"journal":{"name":"Medical Decision Making","volume":" ","pages":"760-773"},"PeriodicalIF":3.1000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10625722/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Decision Making","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/0272989X231188027","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/7/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Highlights: This tutorial provides a user-friendly guide to mathematically formulating constrained optimization problems and implementing them using Python.Two examples are presented to illustrate how constrained optimization is used in health applications, with accompanying Python code provided.
期刊介绍:
Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.