JDE
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

J Dent Educ. 60(1): 47-63 1996
© 1996 American Dental Education Association
This Article
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by White, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by White, S.
Journal of Dental Education, Vol 60, Issue 1, 47-63
Copyright © 1996 by American Dental Education Association

Articles

Decision-support systems in dentistry

SC White

Decision-support systems hold a specialized body of knowledge in computerized form such that the non- specialist can obtain expert-level information. The goal of these systems in clinical sciences is usually to assist patient care by providing the clinician with improved diagnosis or treatment planning. Decision-support systems consist of three components: the user interface through which the clinician or patient enters signs or symptoms, the set of data describing clinical knowledge in the domain of the program, and an inference engine to manipulate the data set in light of a patient's specific signs or symptoms to arrive at a diagnosis or treatment plan. Such systems usually use one of three mechanisms of analysis alone or in combination: classification trees, Bayesian conditional probabilities, or rule-based (heuristic) systems. Numerous problems must be solved before decision-support systems will become commonplace in clinical practice. Data entry of patients' signs and symptoms is often tedious. The quality of the clinician's initial observations is of great importance in determining the quality of the output. It is also often difficult to convey to a program the subtlety of clinical information observed. Knowledge required in clinical data bases is often unavailable or imprecise. As these and other challenges are addressed we can anticipate increased utility of decision support programs in the future.


This article has been cited by other articles:


Home page
 J Dent EducHome page
E. A. Mendonca
Clinical Decision Support Systems: Perspectives in Dentistry
J Dent Educ., June 1, 2004; 68(6): 589 - 597.
[Abstract] [Full Text] [PDF]

Home page
 Adv. Dent. Res.Home page
T.K. Schleyer
Dental Informatics: An Emerging Biomedical Informatics Discipline
Adv. Dent. Res., December 1, 2003; 17(1): 4 - 8.
[Abstract] [Full Text] [PDF]

Home page
 Adv. Dent. Res.Home page
T.K. Schleyer
Dental Informatics: A Work in Progress
Adv. Dent. Res., December 1, 2003; 17(1): 9 - 15.
[Abstract] [Full Text] [PDF]

Home page
 Journal of the American Dental AssociationHome page
T. K.L. SCHLEYER, H. SPALLEK, W. C. BARTLING, and P. CORBY
The technologically well-equipped dental office
J Am Dent Assoc, January 1, 2003; 134(1): 30 - 41.
[Abstract] [Full Text] [PDF]

Home page
 J. Dent. Res.Home page
A. Wenzel
Two Decades of Computerized Information Technologies in Dental Radiography
J. Dent. Res., September 1, 2002; 81(9): 590 - 593.
[Full Text] [PDF]

Home page
 Journal of the American Dental AssociationHome page
T. SCHLEYER and H. SPALLEK
Dental informatics: A cornerstone of dental practice
J Am Dent Assoc, May 1, 2001; 132(5): 605 - 613.
[Abstract] [Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 1996 by the American Dental Education Association.