Model Dermatol – Skin Disease

2.91K reviews
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About this app

Artificial intelligence can analyze the provided photograph and instantly help to find medical information for your skin problem. The algorithm offers relevant medical information on skin diseases (e.g. wart, shingles), skin cancer (e.g. melanoma), and other skin rashes (e.g. hive).

- Please capture skin photographs and submit them for analysis. The cropped images will be transferred, but we will not store your data.
- The algorithm provides links to websites that describe the relevant signs and symptoms of skin disease and skin cancer (e.g. melanoma).
- With the ability to classify images of 186 skin diseases, the algorithm covers common types of skin disorders such as atopic dermatitis, hive, eczema, psoriasis, acne, rosacea, wart, onychomycosis, shingles, melanoma, and nevus.
- The use of the algorithm is FREE.

However, please keep in mind the following disclaimer:
- This app is an image search tool, NOT A DIAGNOSTIC APP. The disease name provided in the contents of the links is not the final diagnosis of skin cancer or a skin disorder.
- Although the contents are informative, please CONSULT A DOCTOR before making any medical decisions.

We utilize the "Model Dermatology" algorithm. The classifier's performance has been published in several prestigious medical journals. Numerous collaborative studies have been conducted with various hospitals internationally, including Seoul National University, Ulsan University, Yonsei University, Hallym University, Inje University, Stanford, MSKCC, and Ospedale San Bortolo.

- 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
- 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. PLOS One, 2022
- Evaluation of Artificial Intelligence-assisted Diagnosis of Skin Neoplasms – a single-center, paralleled, unmasked, randomized controlled trial. J Invest Dermatol. 2022
Updated on
Jul 13, 2024

Data safety

Safety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.
No data shared with third parties
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No data collected
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Ratings and reviews

2.85K reviews
Liz Lycett
June 25, 2024
Excellent app, easy to use and keeps a history of what the scan finds. Taking a couple of photos of different angles gives a better reading. Highly recommend.
1 person found this review helpful
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Linda Dawson
June 21, 2024
So far so good with this skin App. It diagnosed a skin rash for hub which seems accurate . It Doesn't try to get you to pay monthly for an updated version and only give you one consultation like some do, i sent a few photos and didn't give a limitation. Just waiting for doctors appointment now.
1 person found this review helpful
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Robert Fisher