Literature DB >> 15831413

Improving outcomes in radiology: bringing computer-based decision support and education to the point of care.

Charles E Kahn1.   

Abstract

Many computer applications have been developed in radiology and other medical disciplines to help physicians make decisions. Artificial intelligence (AI)--an approach to computer-based manipulation of symbols to simulate human reasoning--forms the basis of many of these systems. This article's goals are to: acquaint the reader with the motivations and opportunities for computer-based medical decision support systems; identify AI techniques and applications in radiology decision making; assess the impact of these technologies; and consider new directions and opportunities for AI in radiology. Among the exciting new directions is the use of AI to integrate radiology reporting, online decision support, and just-in-time learning to provide useful information and continuing education that is embedded within a radiologist's daily workflow.

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Year:  2005        PMID: 15831413     DOI: 10.1016/j.acra.2004.12.025

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  2 in total

1.  A presentation system for just-in-time learning in radiology.

Authors:  Charles E Kahn; Amadeu Santos; Cheng Thao; Jayson J Rock; Paul G Nagy; Kevin C Ehlers
Journal:  J Digit Imaging       Date:  2007-03       Impact factor: 4.056

2.  Medical imaging informatics: how it improves radiology practice today.

Authors:  J Raymond Geis
Journal:  J Digit Imaging       Date:  2007-02-16       Impact factor: 4.056

  2 in total

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