Literature DB >> 1752121

An approach to evaluating the accuracy of DXplain.

M J Feldman1, G O Barnett.   

Abstract

DXplain is a computer-based decision support system which generates a differential diagnosis (ddx) from a given list of clinical manifestations (Barnett et al., J. Am. Med. Assoc. 258 (1987) 67-74). An approach was developed to evaluate the accuracy of the ddx's produced by DXplain. The first step involves the collection of 65 benchmark cases drawn from a variety of sources and authors. Despite their diverse origins, the cases share in common that they are all clinical cases upon which a consulting physician might be asked to produce a differential. This helps to ensure that the evaluation of the system will be done in an environment similar to that in which the system is actually used. In the second step, all cases are reviewed by five board-certified physicians (experts) as well as DXplain. For each case, the evaluators (experts and DXplain) produce a rank-ordered ddx list along with an indication of how strongly each disease was felt to be supported by the case findings. A scoring technique was devised which rewards concordance with the gold standard: a consensus of the evaluators' ddx lists. Each evaluator receives a score which is proportional to the degree of agreement achieved with the consensus on the ddx submitted. Preliminary results on a trial evaluation of 46 cases indicate that DXplain, on average, did well in agreeing with the consensus. Agreement was achieved both in regard to the specific diagnoses listed in the ddx and the degree to which the diseases were felt to be supported by the case findings. A discussion of some important issues in the evaluation of knowledge-based systems is undertaken.

Mesh:

Year:  1991        PMID: 1752121     DOI: 10.1016/0169-2607(91)90004-d

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  14 in total

1.  Influence of case and physician characteristics on perceptions of decision support systems.

Authors:  E S Berner; R S Maisiak
Journal:  J Am Med Inform Assoc       Date:  1999 Sep-Oct       Impact factor: 4.497

2.  Effects of a decision support system on physicians' diagnostic performance.

Authors:  E S Berner; R S Maisiak; C G Cobbs; O D Taunton
Journal:  J Am Med Inform Assoc       Date:  1999 Sep-Oct       Impact factor: 4.497

3.  Impact of a computer-based diagnostic decision support tool on the differential diagnoses of medicine residents.

Authors:  Mitchell J Feldman; Edward P Hoffer; G Octo Barnett; Richard J Kim; Kathleen T Famiglietti; Henry C Chueh
Journal:  J Grad Med Educ       Date:  2012-06

Review 4.  The basis for using the Internet to support the information needs of primary care.

Authors:  E E Westberg; R A Miller
Journal:  J Am Med Inform Assoc       Date:  1999 Jan-Feb       Impact factor: 4.497

5.  Relationships among performance scores of four diagnostic decision support systems.

Authors:  E S Berner; J R Jackson; J Algina
Journal:  J Am Med Inform Assoc       Date:  1996 May-Jun       Impact factor: 4.497

6.  Integrating DXplain into a clinical information system using the World Wide Web.

Authors:  G Elhanan; S A Socratous; J J Cimino
Journal:  Proc AMIA Annu Fall Symp       Date:  1996

7.  Presence of key findings in the medical record prior to a documented high-risk diagnosis.

Authors:  Mitchell J Feldman; Edward P Hoffer; G Octo Barnett; Richard J Kim; Kathleen T Famiglietti; Henry Chueh
Journal:  J Am Med Inform Assoc       Date:  2012-03-19       Impact factor: 4.497

Review 8.  Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary.

Authors:  R A Miller
Journal:  J Am Med Inform Assoc       Date:  1994 Jan-Feb       Impact factor: 4.497

9.  Iliad and Medical HouseCall: evaluating the impact of common sense knowledge on the diagnostic accuracy of a medical expert system.

Authors:  O Bouhaddou; J G Lambert; G E Morgan
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1995

Review 10.  Artificial intelligence in medicine and male infertility.

Authors:  D J Lamb; C S Niederberger
Journal:  World J Urol       Date:  1993       Impact factor: 4.226

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