Skin diseases are emerging as severe problems among people. Can AI and ML will extend its hand to deal with it?
FREMONT, CA: Dermatology is the branch of medicine that emphasizes the evaluation and diagnosis of skin disorders, including nails and hair.
The scientists are trying to dig out ways of using AI for prior detection of skin diseases and to increase clinician capacity efficiently.
Most of the AI-use cases and evolving applications in dermatology fall into two main categories:
• Skin image analysis: Organizations are developing devices and applications utilizing computer vision and machine learning to analyze images to forecast and avoid the onset of skin disease.
•Skincare treatment personalization: Organizations are developing recommendation engines to modify skincare treatment recommendations to customer’s skin type.
SKIN IMAGE ANALYSIS
1. Skin IO
Designed by ECD-Network, Skin IO is an app that utilizes deep learning technology to look for skin cancer through mobile devices.
The application’s algorithm is trained on an extended clinical image database of skin conditions.
Patients initiate by installing the Skin IO application and signing up with the Skin IO’s network.
Users click pictures of the areas of the body that they wish to get evaluated. Besides, the system is designed to process whole body regions. These kinds of scans seem to be integrated, utilizing an overlay feature in the application camera.
The users are instructed to submit follow-up photos within predetermined time frames to track any possible growths or changes on the skin that can be the symptom of skin cancer or other skin diseases. The system also set reminders for the users to submit photos for analysis.
The mobile app makes use of machine vision to keep a check on skin lesions for cancer risk via photo analysis.
The algorithm is trained on a database of around 1 million images of skin lesions, thereby knowing how to recognize particular features like size, shape, and color and which ones might indicate a higher risk of melanoma.
When a user clicks a picture of a lesion via the app, the algorithm groups the lesion as low, low with symptoms, or high, and provides step by step advice for seeking a diagnosis. All risk indications are reviewed and quality assured by dermatologists and experts at SkinVision.
This app utilizes machine learning to evaluate and track the transformations and developments of moles on the skin.
The device helps in the prior detection of some severe skin conditions like melanoma. Users enable the application by connecting the MoleScope apparatus to their smartphone.
Once connected, the users can scan their moles with the device and send high definition pictures to their dermatologist for analysis. Also, it offers step-by-step instructions for self-check moles to users.
After the submission of other scans, users also have the privilege of interacting with their dermatologist via MoleScope for more instructions. This application also assists care providers’ workflow management through its scheduling platform.
SKINCARE TREATMENT PERSONALIZATION
1. PROVEN Beauty
PROVEN Beauty, a California-based startup, claims to offer machine learning benefits to establishing customized cosmetic skincare products.
The algorithm of the company is trained on a huge skincare information database called the Beauty Genome Project.
The users start by finishing a series of questions via the company’s website to help develop their special skin profile. Examples of data points allocated include the level of water intake, ethnicity and skin type, and skincare objectives.
After completing the short questionnaire, users sign up to review their results and customized skincare products.
2. Hello Ava
The chatbot AVA of HelloAva Inc. uses AI to analyze user skin type and advice cosmetic skincare products.
The algorithm of chatbots is trained to utilize dermatology resources from Mt. Sinai Hospital in New York. The questions are framed to reflect those utilized during a patient visit in a clinic setting.
The users can access the platform via both SMS text messaging and Facebook Messenger. The platform starts with a series of 12 question prompts, enabling the chatbots to group the user’s skin type among 30 different variations. Later, the information collected can be used to make particular skincare product recommendations.
Users can also connect with a human advisor to have a more in-depth insight on the recommendations. At the end of the communication, users are given a direct link to buy the products.
Seeing the above technologies, it is easy to make out that machine learning and AI have a remarkable impact on the dermatology industry, and the effect will continue to increase.