4 Applications of Artificial Intelligence (AI) on Dermatology

The role of artificial intelligence (AI) is only getting started in the healthcare industry, with industries such as dermatology benefiting greatly from the advancements of the technology. With AI and machine learning (ML), doctors can better distinguish between different moles and skin conditions. The technology also offers analytical tools to help determine the details of a skin condition, as well as potential treatment routes.

Intelligent automation company WorkFusion offers a Smart Process Automation (SPA) platform that helps businesses in the healthcare industry automate work processes. The business can help companies reduce manual labor by up to 90% and the dermatology industry is set to benefit greatly from this technology.

Here are four applications of AI in dermatology:

1) Better Identify Illnesses

Companies such as DermEngine have developed advanced dermatology software that uses AI algorithms and content-based image retrieval (CBIR) to automatically identify labeled images that look similar to a patient’s case visually. The technology can help to reduce the amount of time between a patient visiting a clinic and receiving the appropriate feedback to get their condition treated as this process can take up to a year.

DermEngine has a Visual Search engine that offers dermatologists clear dermoscopic images, analytics on visually similar cases, as well as statistics that reveal the risks of malignancy based on past imaged.

2) Skin Image Analysis

Netherlands-based SkinVision has also made great strides with a mobile app that uses machine vision to check for skin lesions to determine cancer risk through photo analysis. The app has been trained using a deep learning model that examines over 1 million images of skin lesions, helping it to recognize unique features of a condition such as size, color and shape.

When a user uses the app to take a photo, an ML algorithm categorizes the lesion as low, medium or high risk. It also offers treatment recommendations, such as the contact information of dermatologists that can help with a particular condition.

3) Skin Cancer Analysis

Chicago-based ECD-Network has created a similar app called Skin IO that uses deep learning technology specifically to screen for skin cancer through mobile devices. The app uses an algorithm that has amassd data from a wide database of clinical images of skin conditions, although it is unclear as to where the images were sourced from.

Patients can download the app, take photos of their mole and have it analyzed. The app can also process entire body regions, which can be integrated using an overlay feature in the app camera.

4) Skincare Treatment Personalization

California-based startup PROVEN Beauty uses machine learning to offer consumers customized cosmetic skin care products. The algorithm uses information from a large skincare database known as the Beauty Genome Project, which reportedly includes 8 million customer reviews, 100,000 skincare projects and 20,000 ingredients.

The site asks users to answer questions about their skin profile such as ethnicity, skin type, level of water intake and skincare goals. The questionnaire then offers results and personalized skincare products.