Intel Labs AI Reference Kits for Next-Gen Health Tech

The application aids in the early diagnosis of illnesses using X-ray pictures and symptom descriptions. For model optimization, it makes use of oneAPI libraries and Intel AI Reference Kits

The intrinsic constraint of current healthcare solutions designed exclusively for particular GPUs served as the driving force behind the creation of the Healthcare AI Reference Kits Companion

In order to construct the Healthcare AI Reference Kits Companion, oneAPI tools with cross-architecture were utilized

Convolutional layers are optimized by the library, which is essential for improving the effectiveness of illness identification in X-ray pictures

Although not the main goal, oneDAL helps to improve feature engineering and guarantee data quality, which are essential for precise disease detection models

The Intel Extension for PyTorch allows for mixed-precision training without compromising accuracy, optimizes model training, and speeds up deep learning workloads on Intel CPUs