Zhang / Zhou / Yue So Advances in Artificial Intelligence: Efficiency, Reliability, and Innovations in Machine Learning to Healthcare, and Blockchain
Erscheinungsjahr 2026
ISBN: 978-3-032-12362-6
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 195 Seiten
Reihe: Adaptation, Learning, and Optimization
ISBN: 978-3-032-12362-6
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
1. EM Algorithm for Tensor Network Logistic Regression based on Polya-Gamma Augmentation.- 2. Reproducibility Analysis for Results of Coupled Tensor Decompositions Based on Federated Learning.- 3. Image-based Skin Disease Classification Using Transfer Learning Model and Fusion Strategy.- 4. A High Precision Symptom Prediction and Diagnosis of Atrial Fibrillation Using CNN and LSTM with Multimodal Feature Fusion Technique.- 5. Personalised Profiling in Mental Health: A CAT-based Approach for Maternal Well-being and Mood Disorders.
