Michael W. Kattan – författare
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3 produkter
3 produkter
777 kr
Skickas inom 10-15 vardagar
Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient’s individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest.Features:All you need to know to correctly make an online risk calculator from scratch. Discrimination, calibration, and predictive performance with censored data and competing risks. R-code and illustrative examples. Interpretation of prediction performance via benchmarks. Comparison and combination of rival modeling strategies via cross-validation.
2 176 kr
Skickas inom 10-15 vardagar
Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient’s individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest.Features:All you need to know to correctly make an online risk calculator from scratch. Discrimination, calibration, and predictive performance with censored data and competing risks. R-code and illustrative examples. Interpretation of prediction performance via benchmarks. Comparison and combination of rival modeling strategies via cross-validation.
6 198 kr
Tillfälligt slut
Decision making is a critical element in the field of medicine that can lead to life-or-death outcomes, yet it is an element fraught with complex and conflicting variables, diagnostic and therapeutic uncertainties, patient preferences and values, and costs. Together, decisions made by physicians, patients, insurers, and policymakers determine the quality of health care, quality that depends inherently on counterbalancing risks and benefits and competing objectives such as maximizing life expectancy versus optimizing quality of life or quality of care versus economic realities.Broadly speaking, concepts in medical decision making (MDM) may be divided into two major categories: prescriptive and descriptive. Work in the area of prescriptive MDM investigates how medical decisions should be done using complicated analyses and algorithms to determine cost-effectiveness measures, prediction methods, and so on. In contrast, descriptive MDM studies how decisions actually are made involving human judgment, biases, social influences, patient factors, and so on. The Encyclopedia of Medical Decision Making gives a gentle introduction to both categories, revealing how medical and healthcare decisions are actually made—and constrained—and how physician, healthcare management, and patient decision making can be improved to optimize health outcomes.Key FeaturesDiscusses very general issues that span many aspects of MDM, including bioethics; health policy and economics; disaster simulation modeling; medical informatics; the psychology of decision making; shared and team medical decision making; social, moral, and religious factors; end-of-life decision making; assessing patient preference and patient adherence; and moreIncorporates both quantity and quality of life in optimizing a medical decisionConsiders characteristics of the decisionmaker and how those characteristics influence their decisionsPresents outcome measures to judge the quality or impact of a medical decisionExamines some of the more commonly encountered biostatistical methods used in prescriptive decision makingProvides utility assessment techniques that facilitate quantitative medical decision makingAddresses the many different assumption perspectives the decision maker might choose from when trying to optimize a decisionOffers mechanisms for defining MDM algorithmsWith comprehensive and authoritative coverage by experts in the fields of medicine, decision science and cognitive psychology, and healthcare management, this two-volume Encyclopedia is a must-have resource for any academic library.