Skin Diseases affect people globally and have widespread effects on physical health and emotional well-being. One of the significant challenges is diagnosing rare skin health cases. The role of AI powered algorithms and LLM models have emerged as valuable tools in diagnosing skin diseases more accurately.
Rajat Balyan and Shubham Tiwary in their blog proposed a solution for identifying and classifying different skin diseases, as well as further providing symptoms and suggestions for encouraging further diagnosis with a medical professional. They have developed this project using TensorFlow* Optimizations from Intel and Intel® Tiber™ Developer Cloud.
The blog explains the various steps involved in the project:
- Image Classification - CNN Model
- LLM (RAG) based Symptom Checker & Recommendation
Read more about the project on Medium and GitHub.
Learn more about TensorFlow Optimizations from Intel
Intel collaborates with Google* to upstream most optimizations into the stock distribution of TensorFlow with the newest optimizations and features being released earlier as Intel® Extension for TensorFlow*. These optimizations can be enabled with a few lines of code and will accelerate TensorFlow-based training and inference performance on Intel CPU and GPU hardware.
What’s Next?
We encourage you to check out and incorporate Intel’s other AI/ML Framework optimizations and tools into your AI workflow and learn about the unified, open, standards-based oneAPI programming model that forms the foundation of Intel’s AI Software Portfolio to help you prepare, build, deploy, and scale your AI solutions.
About the Author:
Rajat Balyan and Shubham Tiwary are currently pursuing their bachelors in computer science at Uttaranchal University. They are passionate about data science and Artificial Intelligence.
Product Marketing Engineer bringing cutting edge AI/ML solutions and tools from Intel to developers.