This is an EXPERIMENTAL DEMO APP for Medical Professionals.
This program will predict whether the image looks like melanoma.
The results obtained with this program are for research purpose only.
Please check with your dermatologist for accurate diagnosis.
** THIS DEMO CANNOT CONFIRM THAT THE SUBMITTED IMAGE IS NOT SKIN CANCER. Approximately 10% of skin cancer can be missed if diagnosis is based on clinical photography alone.
** The photographs used for analysis are transferred, and stored and can be used as research data for new service research and development.
** This DEMO produce a sub-optimal performance for the images of non-medical professionals. Please be sure to take pictures in bright places.
– Malignancy Prediction
The app will display the result text according to the following conditions:
1) “Probably Not”, Observation and follow-up : miss rate – 0 ~ 6.5%
2) “Possibly”, Biopsy recommended : miss rate – 6.5 ~ 19%
3) “Likely”, Biopsy recommended : miss rate – 19 ~ 50%
4) “Very Likely”, Biopsy recommended : miss rate – 50 ~ 100%
cf) miss rate (false negative rate) = 1 – sensitivity; The two scores (output and index) in parentheses must satisfy the condition at the same time.
– Raw outputs
q – image quality output
n – image nodularity output
M – malignancy output, index
S – steroid output, index
A – antibiotics output,index
V – antivirals output,index
F – antifungals output,index
The model has approximately 90% accuracy (sensitivity and specificity) for melanoma detection.
The AUC (area under ROC curve) value for melanoma detection with the images of melanoma and nevus is approximately 0.96.