Model Dermatol - Wiki Reviews

- Augment Intelligence Dermatology : Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders.

Artificial intelligence provides relevant medical information on skin disease (e.g. skin rash, wart, hive) and skin cancer (e.g. melanoma).

Artificial intelligence provides personalized links to websites that describe the signs and symptoms of skin disease and skin cancer (e.g. melanoma).

* "Model Dermatology" will provide relevant information on dermatology clinics, skin disease, and skin cancer.

- Assessment of Deep Neural Networks for the Diagnosis of Benign and Malignant Skin Neoplasms in Comparison with Dermatologists: A Retrospective Validation Study.

- A total of 10% of cases of skin cancer can be missed if the diagnosis was made using clinical images alone.

- Keratinocytic Skin Cancer Detection on the Face using Region-based Convolutional Neural Network.

* The algorithm can classify 184 skin diseases which include common types of skin disorders (e.g. atopic dermatitis, hives, eczema, psoriasis, acne, rosacea, onychomycosis, melanoma, nevus).

- Evaluation of Artificial Intelligence-assisted Diagnosis of Skin Neoplasms – a single-center, paralleled, unmasked, randomized controlled trial.

- The prediction of the algorithm is not the final diagnosis of skin cancer or skin disorder.

- Augmenting the Accuracy of Trainee Doctors in Diagnosing Skin Lesions Suspected of Skin Neoplasms in a Real-World Setting: A Prospective Controlled Before and After Study.

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

- Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

Artificial intelligence also gives information on the appropriate dermatology clinic.