Model Dermatology

Experimental DEMO of artificial intelligence in dermatology. High Speed Oversea Internet Connection is required to run the online algorithm. Please check the internet connection if it does not work. Artificial intelligence scans the given photos and instantly advises on your skin problems. AI gives risk information associated with the specific lesion. ♦ Capture skin photographs and submit. ♦ "Model Dermatology" can classify 184 skin diseases. ♦ "Model Dermatology" will provide information on skin disease and dermatology clinic. AI provides links to websites that describe the signs and symptoms of skin diseases. ♦ "Model Dermatology" will perform the visual assessment of the bizarreness of the lesion and gives risk information. The Top-1/3/5 accuracy using the Edinburgh data set (White population; 1300 images; 10 tumorous skin disorders) are 61.0%/81.6%/89.2%. The Top-1/3/5 accuracy using the SNU data set (Asian; 2201 images; 134 skin disorders) are 54.7%/77.0%/84.7% without metadata of basic symptoms, and 64.6%/85.2%/91.8% with the basic symptoms. The algorithm, "Model Dermatology" can classify 184 skin diseases which include most kinds of skin cancers and inflammatory disorders (e.g. skin rash). The performance of the skin disease classifier was published in several medical journals. ** Papers for the Model Dermatology ** - Assessment of Deep Neural Networks for the Diagnosis of Benign and Malignant Skin Neoplasms in Comparison with Dermatologists: A Retrospective Validation Study. PLOS Medicine, 2020 - Performance of a deep neural network in teledermatology: a single‐center prospective diagnostic study. J Eur Acad Dermatol Venereol. 2020 - Keratinocytic Skin Cancer Detection on the Face using Region-based Convolutional Neural Network. JAMA Dermatol. 2019 - Seems to be low, but is it really poor? : Need for Cohort and Comparative studies to Clarify Performance of Deep Neural Networks. J Invest Dermatol. 2020 - Multiclass Artificial Intelligence in Dermatology: Progress but Still Room for Improvement. J Invest Dermatol. 2020 - Augment Intelligence Dermatology : Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders. J Invest Dermatol. 2020 - Interpretation of the Outputs of Deep Learning Model trained with Skin Cancer Dataset. J Invest Dermatol. 2018 - Automated Dermatological Diagnosis: Hype or Reality? J Invest Dermatol. 2018 - Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm. J Invest Dermatol. 2018