Biomaterial Database

Comparison of pattern recognition methods for computer-assisted classification of spectra of heart sounds in patients with a porcine bioprosthetic valve implanted in the mitral position. 1990

L G Durand, and M Blanchard, and G Cloutier, and H N Sabbah, and P D Stein

Laboratory of Biomedical Engineering, Clinical Research Institute of Montreal, P.Q., Canada.

The diagnostic performance of two pattern recognition methods (or classifiers) to detect valvular degeneration was evaluated in 48 patients with a porcine bioprosthetic heart valve inserted in the mitral position. Twenty patients had a normal porcine bioprosthetic valve and 28 patients had a degenerated bioprosthetic valve. One method was based on the Gaussian-Bayes model and the second on the "nearest neighbor" algorithm using three distance measurements. Eighteen diagnostic features were extracted from the sound spectrum of each patient and, for each method, a two-class supervised learning approach was used to determine the most discriminant diagnostic patterns composed of 6 features or less. The probability of error of the classifiers was estimated with the leave-one-out approach. The performance of each method to discriminate between normal and degenerated bioprosthetic valves was verified by clinical evaluation of the valves. The best performance in evaluation of the sound spectrum (98% correct classifications) was obtained with the Bayes classifier and two patterns of six features each. The percentage of false positive classifications of valve degeneration was 0% and the percentage of false negative classifications was 4%. Sensitivity for the detection of valve degeneration was 96%, specificity was 100%, positive predictive value was 100%, and negative predictive value was 95%. The best performance of the nearest neighbor method (94% correct classifications) was obtained by using the Mahalanobis distance and five patterns composed of three, four, five, or six diagnostic features. Using a pattern composed of only three features, the percentage of false positive classifications for degeneration was 10% and the percentage of false negative classifications was 4%.(ABSTRACT TRUNCATED AT 250 WORDS)

UI	MeSH Term	Description	Entries
D008943	Mitral Valve	The valve between the left atrium and left ventricle of the heart.	Bicuspid Valve,Bicuspid Valves,Mitral Valves,Valve, Bicuspid,Valve, Mitral,Valves, Bicuspid,Valves, Mitral
D010363	Pattern Recognition, Automated	In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed)	Automated Pattern Recognition,Pattern Recognition System,Pattern Recognition Systems
D010701	Phonocardiography	Graphic registration of the heart sounds picked up as vibrations and transformed by a piezoelectric crystal microphone into a varying electrical output according to the stresses imposed by the sound waves. The electrical output is amplified by a stethograph amplifier and recorded by a device incorporated into the electrocardiograph or by a multichannel recording machine.	Phonocardiographies
D011237	Predictive Value of Tests	In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test.	Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D011475	Prosthesis Failure	Malfunction of implantation shunts, valves, etc., and prosthesis loosening, migration, and breaking.	Prosthesis Loosening,Prosthesis Durability,Prosthesis Migration,Prosthesis Survival,Durabilities, Prosthesis,Durability, Prosthesis,Failure, Prosthesis,Failures, Prosthesis,Loosening, Prosthesis,Loosenings, Prosthesis,Migration, Prosthesis,Migrations, Prosthesis,Prosthesis Durabilities,Prosthesis Failures,Prosthesis Loosenings,Prosthesis Migrations,Prosthesis Survivals,Survival, Prosthesis,Survivals, Prosthesis
D003936	Diagnosis, Computer-Assisted	Application of computer programs designed to assist the physician in solving a diagnostic problem.	Computer-Assisted Diagnosis,Computer Assisted Diagnosis,Computer-Assisted Diagnoses,Diagnoses, Computer-Assisted,Diagnosis, Computer Assisted
D006347	Heart Sounds	The sounds heard over the cardiac region produced by the functioning of the heart. There are four distinct sounds: the first occurs at the beginning of SYSTOLE and is heard as a "lubb" sound; the second is produced by the closing of the AORTIC VALVE and PULMONARY VALVE and is heard as a "dupp" sound; the third is produced by vibrations of the ventricular walls when suddenly distended by the rush of blood from the HEART ATRIA; and the fourth is produced by atrial contraction and ventricular filling.	Cardiac Sounds,Cardiac Sound,Heart Sound,Sound, Cardiac,Sound, Heart,Sounds, Cardiac,Sounds, Heart
D006350	Heart Valve Prosthesis	A device that substitutes for a heart valve. It may be composed of biological material (BIOPROSTHESIS) and/or synthetic material.	Prosthesis, Heart Valve,Cardiac Valve Prosthesis,Cardiac Valve Prostheses,Heart Valve Prostheses,Prostheses, Cardiac Valve,Prostheses, Heart Valve,Prosthesis, Cardiac Valve,Valve Prostheses, Cardiac,Valve Prostheses, Heart,Valve Prosthesis, Cardiac,Valve Prosthesis, Heart
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001499	Bayes Theorem	A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.	Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes