Comparisons of the abilities of a neural network and three consultant oral surgeons to make decisions about third molar removal.

AIM

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.

DESIGN AND SETTING

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

SUBJECTS AND 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.

MAIN OUTCOME MEASURES

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.