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PubMed · 9922949

A network-based training environment: a medical image processing paradigm.

L Costaridou·G Panayiotakis·P Sakellaropoulos·D Cavouras·J Dimopoulos
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Abstract

The capability of interactive multimedia and Internet technologies is investigated with respect to the implementation of a distance learning environment. The system is built according to a client-server architecture, based on the Internet infrastructure, composed of server nodes conceptually modelled as WWW sites. Sites are implemented by customization of available components. The environment integrates network-delivered interactive multimedia courses, network-based tutoring, SIG support, information databases of professional interest, as well as course and tutoring management. This capability has been demonstrated by means of an implemented system, validated with digital image processing content, specifically image enhancement. Image enhancement methods are theoretically described and applied to mammograms. Emphasis is given to the interactive presentation of the effects of algorithm parameters on images. The system end-user access depends on available bandwidth, so high-speed access can be achieved via LAN or local ISDN connections. Network based training offers new means of improved access and sharing of learning resources and expertise, as promising supplements in training.

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Computer Communication NetworksComputer SystemsComputer-Assisted InstructionEducation, DistanceImage Processing, Computer-AssistedInternetMultimediaJournal ArticleResearch Support, Non-U.S. Gov't

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L Costaridou, G Panayiotakis, P Sakellaropoulos, D Cavouras, J Dimopoulos. A network-based training environment: a medical image processing paradigm.. https://doi.org/10.3109/14639239809025365

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PubMed2000

Does the structure of clinical questions affect the outcome of curbside consultations with specialty colleagues?

BACKGROUND: Clinical questions frequently arise during the practice of medicine, and primary care physicians frequently use curbside consultations with specialty physicians to answer these questions. It is hypothesized that well-formulated clinical questions are more likely to be answered and less likely to receive a recommendation for formal consultation. OBJECTIVE: To assess the relationship between the structure of clinical questions asked by family physicians and the response of specialty physicians engaged in curbside consultations. DESIGN AND PARTICIPANTS: A case series of clinical questions asked during informal consultations between 60 primary care and 33 specialty physicians using an e-mail service. Curbside consultation questions were sent, using e-mail, to academic specialty physicians by primary care physicians (faculty, residents, and community practitioners) in eastern Iowa. MAIN OUTCOME MEASURES: Questions were analyzed to determine the clinical task and to identify 3 components: an intervention, a comparison, and an outcome. Consultants' responses were analyzed to identify whether questions were answered and whether consultants recommended formal consultation. RESULTS: There were 708 questions in this analysis: 278 (39.3%) were diagnosis questions, 334 (47.2%) were management questions, 57 (8.0%) were prognosis questions, and 39 (5.5%) were requests for direction. Clinical questions were less likely to go unanswered or receive a recommendation for formal consultation when the question identified the proposed intervention (odds ratio, 0.54; 95% confidence interval, 0.34-0.86; P = .006) and desired outcome (odds ratio, 0.46; 95% confidence interval, 0.29-0.69; P < .001). Only 271 (38.3%) of 708 curbside consult questions identified both of these components. CONCLUSION: Medical specialists' responses to curbside consultation questions seem to be affected by the structure of these clinical questions.

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