Advances in Artificial Intelligence: Efficiency, Reliability, and Innovations in Machine Learning to Healthcare, and Blockchain
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Adaptation, Learning, and Optimization
Advances in Artificial Intelligence: Efficiency, Reliability, and Innovations in Machine Learning to Healthcare, and Blockchain
Jingfeng Zhang | Joey Zhou | Rosa Qi Yue So | Takaharu Yaguchi | Kentaroh Toyoda | Andong Wang | Peilun Dai | Haotong Qing | Xingyu Zheng
Artificial intelligence is transforming the way we live, work, and heal. But true progress depends on more than raw power—it requires systems that are efficient, reliable, and trustworthy.
Advances in Artificial Intelligence: Efficiency, Reliability, and Innovations in Machine Learning, Healthcare, and Blockchain explores cutting-edge breakthroughs across machine learning, healthcare, and blockchain. From interpretable tensor models and life-changing medical applications to secure decentralized learning and safer large language models, this book highlights how innovation can meet responsibility.
Written by leading researchers, this book is an essential resource for anyone looking to understand and shape the next generation of AI.
| Publication Date: | 15 May 2026 |
| Publisher: | Springer Nature Switzerland |
| Imprint: | Springer |
| ISBN-13: | 9783032123619 |
| Format: | Hardback |
| Page Count: | 195 |