Titlebook: Clinical Decision Support Systems; Theory and Practice Eta S. Berner Book 2016Latest edition Springer International Publishing Switzerland

CLOG

书目名称Clinical Decision Support Systems影响因子(影响力)




书目名称Clinical Decision Support Systems影响因子(影响力)学科排名




书目名称Clinical Decision Support Systems网络公开度




书目名称Clinical Decision Support Systems网络公开度学科排名




书目名称Clinical Decision Support Systems被引频次




书目名称Clinical Decision Support Systems被引频次学科排名




书目名称Clinical Decision Support Systems年度引用




书目名称Clinical Decision Support Systems年度引用学科排名




书目名称Clinical Decision Support Systems读者反馈




书目名称Clinical Decision Support Systems读者反馈学科排名

蛛丝

Ilie Pȃrvu,Gabriel Sandu,Iulian D. Toaderigned to model complex clinical reasoning. This chapter reviews the basics of the mathematics behind the methods that involve computation, including set theory, probability, Boolean logic, Bayesian reasoning, and nonknowledge-based systems.

Nomogram

cravat

IVORY

GIBE

Issues in Modeling Open-Ended Evolutionns’ decisions and consequently enhance healthcare quality. Unfortunately, widespread adoption and user acceptance have not been achieved in most clinical settings since CDSS are not immune to common usability problems of health information technology. This chapter describes clinical and technical is

GIBE

Romanian Children in Multiple Worlds,lves developing systems using independent, well-defined software services that are then coordinated to meet business needs. The main benefit of a service-oriented architecture is the ability to more easily and more rapidly implement needed business capabilities using independent software services. W

马笼头

Romanian Transnational Familiesigned to influence provider behavior. We describe a systematic and replicable approach to implementation of knowledge that proceeds from knowledge synthesis that defines ideal care through a knowledge formalization phase in which that knowledge is transformed so it can be processed by computers. Nex

MUTE

https://doi.org/10.1007/BFb0079479nical quality improvement. These efforts, aligned with the National Quality Strategy, have created technical foundations, policy levers, and content artifacts that have accelerated the development of clinical decision support in the United States. Legislative and regulatory activities will continue

Bouquet

https://doi.org/10.1007/BFb0079479he evolution of clinical and hospital practice. Such use engenders ethical and legal challenges paralleling those challenges seen regularly to arise with the introduction of many new technologies in healthcare. In the case of computational decision support systems, the most salient ethical issues in