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Full Description
Efficient Cost Aware Artificial Intelligence in Healthcare and Biomedicine is situated within the broader context of artificial intelligence (AI) and deep learning (DL) technologies as they pertain to healthcare and biomedicine. AI and DL have witnessed remarkable advancements in recent years, leading to breakthroughs in various applications, including medical image analysis, drug discovery, disease diagnosis, and personalized treatment recommendations. In 14 chapters this book offers techniques and best practices for compressing deep learning models, allowing them to run efficiently on healthcare devices with limited memory and processing power. This book provides the void code-first approach to optimizing AI for healthcare and biomedicine by offering practical solutions to the unique challenges posed by AI in healthcare. The growing demand for efficient AI computing techniques, coupled with advancements in Deep Learning and Large Language Models tailored for healthcare and biomedicine, makes this book, Efficient Cost Aware Artificial Intelligence in Healthcare and Biomedicine timely and essential. It addresses the pressing need for practical guidance on compressing and optimizing AI models for everyday healthcare devices, making it accessible to a broad and diverse audience seeking to harness the power of AI within the healthcare and biomedicine sectors. "Efficient AI in Healthcare and Biomedicine" empowers healthcare professionals, researchers, and organizations with practical solutions to the challenges posed by resource-intensive deep learning models in healthcare and biomedicine.
Contents
1. Introduction to Efficient AI Computing in Healthcare
2. Fundamentals of AI Model Efficiency in Biomedicine
3. Model Compression Techniques for Medical Data
4. Distributed Training and Parallelism in Healthcare AI
5. Gradient Compression for Efficient Medical Training
6. On-Device Optimization for Medical Devices
7. Application-Specific Efficiency in Biomedicine
8. Quantum Machine Learning and Efficiency in Biomedicine
9. Performance Optimization with PyTorch in Healthcare AI
10. Advances in Model Efficiency for Biomedicine
11. Mixture of Experts Models in Healthcare AI
12. Managing Resource Constraints in Medical AI
13. Interviews with Industry Leaders in Healthcare AI
14. Future Trends and Challenges in Healthcare AI
