title: Computer probability estimates of angiographic coronary artery disease: transportability and comparison with cardiologists' estimates.
abstract: A computer algorithm for estimating probabilities of any significant coronary obstruction and triple vessel/left main obstructions was derived, validated, and compared with the assessments of cardiac clinician angiographers. The algorithm performed at least as well as the clinicians when the latter knew the identity of the patients whose angiograms they had decided to perform. The clinicians were more accurate when they did not know the identity of the subjects but worked from tabulated objective data. Referral and value induced bias may affect physician judgment in assessing disease probability. Application of computer aids or consultation with cardiologists not directly involved with patient management may assist in more rational assessments and decision making.
authors.affiliation: Department of Medicine, Saint John's Cardiovascular Research Center, Harbor-UCLA Medical Center, Torrance 90502.
authors.forename: R
authors.initials: R
authors.lastname: Detrano
authors.forename: M
authors.initials: M
authors.lastname: Bobbio
authors.forename: H
authors.initials: H
authors.lastname: Olson
authors.forename: A
authors.initials: A
authors.lastname: Shandling
authors.forename: M H
authors.initials: MH
authors.lastname: Ellestad
authors.forename: E
authors.initials: E
authors.lastname: Alegria
authors.forename: D
authors.initials: D
authors.lastname: Martinez-Caro
authors.forename: A
authors.initials: A
authors.lastname: Righetti
authors.forename: A
authors.initials: A
authors.lastname: Janosi
authors.forename: W
authors.initials: W
authors.lastname: Steinbrunn
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D017023:Coronary Angiography; D003327:Coronary Disease / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests