Cannataro | The Evolution of Artificial Intelligence in Healthcare | Buch | 978-0-443-33066-7 | www.sack.de

Buch, Englisch, 330 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g

Cannataro

The Evolution of Artificial Intelligence in Healthcare

From Basic Methods to Clinical Practice
Erscheinungsjahr 2027
ISBN: 978-0-443-33066-7
Verlag: Elsevier Science

From Basic Methods to Clinical Practice

Buch, Englisch, 330 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 450 g

ISBN: 978-0-443-33066-7
Verlag: Elsevier Science

The Evolution of Artificial Intelligence in Healthcare: From Basic Methods to Clinical Practice explores revolutionary technological advancements in the medical and healthcare realms due to generative AI and 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. Sections cover foundational concepts and terminologies, explore deep learning and generative AI, provide AI's role in biomedical research, examine its integration into clinical practice, scrutinize its applications in public health, and discuss challenges and future prospects.

This is an indispensable resource for healthcare professionals, scientists, researchers, students, and enthusiasts seeking to deepen their understanding of this rapidly evolving field.

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Autoren/Hrsg.

Cannataro, Mario

Fachgebiete

Weitere Infos & Material

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

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