Comparisons of the abilities of a neural network and three consultant oral surgeons to make decisions about third molar removal.
OBJECTIVE
To compare the performance of a computer based decision support system (a neural network) and consultant oral and maxillofacial surgeons in making decisions about the need to remove lower third molars.


METHODS
Receiver operating characteristic (ROC) analysis at a hospital department of oral and maxillofacial surgery.


METHODS
Three consultant oral and maxillofacial surgeons indicated on a six-point rating scale how certain they were that each of 50 documented lower third molars required removal. Similar data were obtained from the neural network following appropriate coding of the clinical information. These data were compared with gold standard treatment decisions for each tooth based on National Institutes of Health Concensus criteria using ROC analysis.


METHODS
The area beneath each operator ROC curve (varying between zero and one with greater areas indicating better performance).


RESULTS
The network performed as well a two consultants (P = 0.12/0.18, NS) and significantly better than the third (z = 526, P < 0.01).


CONCLUSIONS
This work suggests that this computer based neural network could play a useful role in supporting dental practitioners making third molar referral decisions.
Brickley
M R
MR
Department of Oral Surgery, Medicine and Pathology, Dental School, University of Wales College of Medicine, Heath Park, Cardiff.
Shepherd
J P
JP
D000328:Adult; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008297:Male; D008334:Mandible; D008964:Molar, Third / Q000601:surgery*; D016571:Neural Networks, Computer; D012372:ROC Curve; D012015:Reference Standards; D014081:Tooth Extraction