Skin Disease Classification using Deep Learning Algorithm


Model Dermatology and Model Melanoma

Model Dermatology ( and Model Melanoma ( are our new AI models, which are trained with 220,680 images (174 disease classes).


Model Dermatology API

Model Dermatology API (

Model 12 Skin Tumorous Disorders

Model 12Dx ( is trained with 19,398 manually cropped images and additional 159,477 images (approximately 260 classes).

Original Article – Journal of Investigative of Dermatology (Feb. 2018)

Classification of the clinical images for benign and malignant cutaneous tumors using a deep learning algorithm

Letter – Journal of Investigative of Dermatology (June. 2018)

Interpretation of the Outputs of Deep Learning Model trained with Skin Cancer Dataset


Model Onychomycosis

Model Onychomycosis ( is trained with 49,567 images generated by region-based CNN (R-CNN).
In order to create a deep learning model that demonstrates diagnostic capabilities beyond the specialist, we generated a huge nail dataset by using faster R-CNN.

Android Apps

Android (Model Onychomycosis)

Model Onychomycosis API

Model Onychomycosis API (

Original article – PLoS One (Jan. 2018)

Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network

Magazine – IEEE Spectrum (Feb. 2018)

AI Beats Dermatologists in Diagnosing Nail Fungus


Proximal Humerus Fracture Study

In order to obtain results similar to the specialist with current deep learning models and a small number of data (500 images per class), we should analyze the lesion of interest after cropping the part.

Original article – Acta Orthopaedica (Feb. 2018)

Automated detection and classification of the proximal humerus fracture by using deep learning algorithm



MedicalPhoto is a non-commercial medical image management program. This program was developed for use in dermatology at the Asan Medical Center in 2007 by Han Seung Seog (