## Diagnosing human malformation patterns with a microcomputer: evaluation of two different algorithms

### Détails

ID Serval

serval:BIB_4CC5256668D7

Type

**Article**: article d'un périodique ou d'un magazine.

Collection

Publications

Fonds

Titre

Diagnosing human malformation patterns with a microcomputer: evaluation of two different algorithms

Périodique

American Journal of Medical Genetics

ISSN

0148-7299 (Print)

Statut éditorial

Publié

Date de publication

10/1987

Volume

28

Numéro

2

Pages

337-44

Notes

Comparative Study

Journal Article --- Old month value: Oct

Journal Article --- Old month value: Oct

Résumé

SYNDROC, a microcomputer-aided differential diagnostic approach to human malformation patterns, is based on a pseudo-Bayesian algorithm. This means that, for each sign, the frequency of this sign in the general population, its frequency in a particular syndrome, and the frequency of that particular syndrome have to be determined. These parameters are easy to find in common syndromes but tend to be difficult for rare or isolated cases. Thus, we implemented a new algorithm called the "descriptive algorithm," which defines a diagnosis by a set of anomalies all having the same weight. To test this algorithm, we analyzed 100 cases representing 100 different syndromes out of the register of the Division of Medical Genetics, Children's Hospital and Medical Center, University of Washington. The descriptive algorithm was allowed to give 3 sets of diagnoses. In 91% of the cases, this algorithm proposed the correct diagnosis (54% in the first window, 28% in the second window, and 9% in the third window). The number of diagnoses proposed was 18.78 +/- 16.57. The same cases were analyzed with the pseudo-Bayesian algorithm. The concordant diagnosis was proposed in 92% of the cases (55% at the top place, 11% at the second place, and 26% at the third place or beyond). The number of diagnoses submitted was 13.5 +/- 11.04. The combined algorithm gave the correct diagnosis in 96% of the cases. This study shows that the descriptive algorithm is as accurate as the pseudo-Bayesian algorithm in diagnosing malformation patterns, but this level is accompanied by an increased number of proposed diagnoses.

Mots-clé

Abnormalities, Multiple/*diagnosis *Algorithms Bayes Theorem *Computers Diagnosis, Computer-Assisted/*methods Diagnosis, Differential *Expert Systems Humans *Microcomputers

Pubmed

Web of science

Création de la notice

28/01/2008 13:59

Dernière modification de la notice

18/11/2016 7:18