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