Siya-34/dentalvision-efficientnetb3

DentalVision AI - EfficientNetB3 (v2.0.0)

Multi-label classifier for six findings on dental OPG X-rays (EfficientNetB3 + DenseNet121 + ConvNeXt-Tiny ensemble). Educational and research prototype. Not a diagnostic tool. Predictions must be reviewed by qualified dental professionals.

• Output: 6 independent sigmoid probabilities in this order: 0=Healthy Teeth, 1=Caries, 2=Impacted Teeth, 3=Infection, 4=Fractured Teeth, 5=BDC/BDR. "Healthy Teeth" means the image contains healthy teeth.
• Input: RGB, 288x576 (H x W), bilinear resize, ImageNet mean/std normalisation
• Training: ImageNet transfer learning, BCE with positive class weights, AdamW, cosine schedule, early stopping on validation macro-AUC
• Data: Kaggle imtkaggleteam/dental-opg-xray-dataset (not redistributed): 230 unique radiographs after removing byte-identical copies stored under several class folders.

Results

Evaluation	Macro AUC	mAP	Macro F1
Fold-0 test (n=37)	0.695	0.599	0.508
Pooled 6-fold out-of-fold (230 images)	0.661	0.544	0.503

Limitations

Very small dataset, rare findings, single source, no patient IDs, no external validation.