Artificial intelligence scans certain photos and immediately helps with your skin problems. AI provides relevant medical information on skin diseases (e.g. skin rashes, warts, hives) and skin cancers (e.g. melanoma). AI also provides information on appropriate dermatology clinics. * “Model Dermatology” is regulated as a medical device (CE MDR Class I) on June 22, 2021
◉ Currently not working on some devices due to compatibility issues. If it goes to initial screen without any response or error occurs due to running out of memory, please connect it by going to https://app.skindx.net in Chrome browser.
◉ A high-speed Internet connection is required for use.
♦ Take a photo of the skin and send it.
♦ “Sample Dermatology” will perform a visual assessment of the lesion.
♦ “Sample Dermatology” will provide relevant information on dermatology clinics, skin diseases (eg skin rashes, moles), and skin cancers (eg melanoma) ). AI provides personalized links to web pages that describe the signs and symptoms of skin diseases and skin cancers (e.g., melanoma).
♦ Image cropping and metadata (eg: itching, pain, onset) are transferred, but we do not store your personal data.
♦ A total of 104 multi-languages are supported.
The algorithm can categorize 184 skin diseases, including most skin cancers and inflammatory disorders (eg, skin rashes). The performance of the skin disease classifier has been published in several medical journals.
** Articles on “Model Dermatology” **
– Evaluation of Deep Neural Networks for the diagnosis of benign and malignant skin cancers when compared with dermatologists: Retrospective validation study. PLOS Medicine, 2020
Performance of a deep neural network in teledermatology: a single central prospective diagnostic study. J Eur Acad Dermatol Venereol. Year 2020
– Detection of facial squamous cell skin cancer using region-based Convolutional Neural Networks. JAMA Dermatol. 2019
– Seems to be low, but is it really bad? : Cohort and comparative studies are needed to clarify the performance of deep neural networks. J Investment Dermatol. Year 2020
Multi-glass Artificial Intelligence in Dermatology: Progress but still room for improvement. J Investment Dermatol. Year 2020
Intelligence-enhanced dermatology: Deep neural networks empower medical professionals to diagnose skin cancers and predict treatment options for 134 skin disorders. J Investment Dermatol. Year 2020
– Interpreting Outputs of a Deep Learning Model trained with the Skin Cancer Dataset. J Investment Dermatol. 2018
– Automated Dermatology: Hyperbole or Reality? J Investment Dermatol. 2018
Classification of clinical images for benign and malignant skin tumors using a deep learning algorithm. J Investment Dermatol. 2018
– Improving the accuracy of trainee physicians in diagnosing suspected skin lesions of skin cancer in a real-world setting: A pre- and post-study controlled study. PLOS One, 2022
– Artificial Intelligence-assisted diagnostic evaluation of skin cancer – a single-centre, parallel, randomized controlled trial without a mask. J Investment Dermatol. 2022
** Disclaimer **
– Consult your doctor for an accurate diagnosis.
– The algorithm does not diagnose skin cancer and skin disorders. It only serves to provide personalized medical information for reference.
– A total of 10% of skin cancer cases can be missed with imaging alone, so this app cannot replace the role of standard care.
– Please seek your doctor’s advice beyond using this app and before making any medical decisions.
– The data collection for algorithm improvement is done in the free version.