The Evolution of Artificial Intelligence in Healthcare : From Basic Methods to Clinical Practice

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The Evolution of Artificial Intelligence in Healthcare : From Basic Methods to Clinical Practice

Cannataro, Mario (EDT)

ウェブストア価格 ¥38,684（本体¥35,168）
Elsevier - Health Sciences Division（2026/08発売）
外貨定価 US$ 175.00
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製本 Paperback:紙装版/ペーパーバック版／ページ数 330 p.
言語 ENG
商品コード 9780443330667

Full Description

The Evolution of Artificial Intelligence in Healthcare: From Basic Methods to Clinical Practice delucidates the profound technological advancements revolutionizing the medical and healthcare realms, catalyzed by the advent of generative AI and the maturation of Deep Learning. This comprehensive guide not only explores cutting-edge technologies such as transformers and large language models for newcomers but also demystifies advanced applications like sequential decoding techniques and segmentation algorithms, rarely explored in other literature. Organized into six insightful sections, coverage includes the foundational concepts and terminologies of AI in medicine, explores the realms of deep learning and generative AI, provides AI's role in biomedical research, examines its integration into clinical practices, scrutinizes its applications in public health, and prognosticates the challenges and future prospects of AI in medicine. An indispensable resource for healthcare professionals, scientists, researchers, students, and enthusiasts seeking to deepen their understanding of this rapidly evolving field.

Part I. Artificial Intelligence. basic concepts and definitions
1. Machine Learning and Deep Learning
2. Artificial Neural Networks
3. Data Mining and Data Science

Part II. Artificial Intelligence. deep learning and generative AI
4. Transformers
5. Bidirectional Encoder Representations from Transformers (BERT)
6. Generative AI, Large Language Models
7. GPT. Generative Pre-trained Transformers
8. BARD

Part III. Artificial Intelligence in Biomedical Research
9. Bioinformatics methods and AI.
10. Network Science methods and AI
11. AI for investigating the molecular basis of diseases.
12. AI and Drug Repurposing

Part IV. Artificial Intelligence in Clinical Practice
13. AI based analysis of biosignals
14. AI-based analysis of bioimages
15. AI-based analysis of Medical Reports and Electronic Health Records
16. AI in surgery
17. AI in oncology

Part V. Artificial Intelligence in Public Health
18. One-Health AI
19. Virus diffusion prevention and management

Part VI.
20. Opportunities and Risks of Generative AI (GPT) in Medicine
21. Bias
22. Clinician and Dataset Shift
23. Explainability and Black Box models
24. Privacy and Security
25. Legal and ethical aspects
26. Integrating human and AI knowledge