Skin Disease Detection with AI-Powered Image Recognition

 

Unicsoft’s dedicated team developed a Skin Diagnostic Tool using сomputer vision algorithms, delivering tailored and precise information on skin disorders.

About the Project

The European startup sought to develop an AI solution for early diagnosis of skin disorders, utilizing a cloud-based, computer-aided service. In order to attract major healthcare players and promote the use of AI in healthcare products, the company aimed to build a prototype of an AI application core specifically designed for early diagnosis of the base types of skin disorders.



Business Challenges
The main objective of this project was to build a prototype of an AI application, with the goal of improving patient outcomes within the diagnostics process and enhancing the potential of AI technology in healthcare.
Analyzing complex skin disorders that vary greatly in symptoms, severity, and underlying causes.
Providing value to both patients and specialists with the AI solution, including allowing patients to make decisions in time to get consultations from doctors, and enabling specialists to receive primary diagnostics and recommendations from the AI system.
Ensuring compliance with medical industry regulations and standards.
Creating a cost-effective solution that saves time and money for both the client and end-users.
Demonstrating the capabilities of the solution to specialists in AI, healthcare, and potential investors.
Technical Challenges
The Unicsoft team faced several technical challenges while developing the prototype for skin disorder diagnostic solution, including:
Selecting the optimal algorithm to analyze four types of skin diseases, with the potential for scaling to more types in future iterations.
Collecting free medical images from open source Dermnet.com, a skin diseases library, and processing the images to comply with the model’s needs, including separating the skin and other elements in the photo, highlighting areas with the highest density of problem areas, and scaling to improve the quality of image recognition.
Deploying the prototype in Jupyter notebook, a web-based interactive development environment for creating, sharing, and collaborating on code, and providing all documentation and prototype materials to the client.
Ensuring the solution works in real-time for individual users, with the processes of image recognition and classification model constantly recomputed by an AI Engine.
The Solution
Unicsoft’s R&D team was in charge of developing a prototype for the Skin Diagnostic Model based on Computer Vision algorithms, which required advanced knowledge and expertise in AI and machine learning.
Conducted thorough research and analysis to select the most optimal solution to diagnose early skin problems within the prototype.
Created documentation that estimates the resources and time required to launch this solution into production.
The Result
  • The team created a fully functional prototype of the AI solution, which was delivered to the customer on time and according to the initial requirements.
  • Built a solution that could handle and process thousands of images with disease examples within seconds, and provide primary diagnostics and recommendations to healthcare specialists.
  • Ensured the accuracy and effectiveness of the machine learning model for providing personalized and targeted predictions on skin disorders.

Technology & Tools

CNN
Jupyter
Keras
OpenCV
Python
ML
AI
Computer Vision
Ready to build your AI-powered app?
Contact the expert

More projects

Artificial Intelligence for Skin Cancer
Unicsoft utilized artificial intelligence to build Wellskin solution for accurate skin cancer diagnosis.
Remote Patient Monitoring: Wanda’s AI Prevents Adverse Events 7 Days in Advance
Unicsoft’s expert team collaborated to build an Al-integrated cloud-based platform.