The Evolution of Artificial Intelligence in Healthcare

Nyhet

From Basic Methods to Clinical Practice

Häftad, Engelska, 2026

2 189 kr

Kommande

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.

Shows the main opportunities of using AI in clinical practice and in biomedical research
Gives insight into the main challenges and risks of using AI in clinical practice and in biomedical research
Provides specific requirements for AI systems to be used in biomedical research and clinical practices
Demonstrates legal and ethical aspects of AI systems

Produktinformation

Utgivningsdatum2026-08-01
Mått191 x 235 x undefined mm
FormatHäftad
SpråkEngelska
Antal sidor330
FörlagElsevier Science
ISBN9780443330667

Tillhör följande kategorier

Biologi inom Naturvetenskap och teknik

Mario Cannataro is a Full Professor of Computer Engineering and Bioinformatics at University “Magna Graecia of Catanzaro, Italy. He is the director of the Data Analytics research center and the chair of the Bioinformatics Laboratory. His current research interests include bioinformatics, medical informatics, artificial intelligence, sentiment analysis, data analytics, parallel and distributed computing. He is a member of the editorial boards of Briefings in Bioinformatics and IEEE/ACM Transactions on Computational Biology and Bioinformatics. He was guest editor of several special issues on bioinformatics and health informatics and organized several bioinformatics workshops in conjunction with ACM-BCB and IEEE-BIBM conferences. He has published three books and more than 300 papers in international journals and conference proceedings. Prof. Cannataro is a member of the Ethical Committee of the Calabria Region and a senior member of ACM, IEEE and SIBIM, He is currently a member of the steering committee of the Italian Bioinformatics Society (BITS) and of the Italian Association for Telemedicine and Medical Informatics (AITIM).

Part I. Artificial Intelligence. basic concepts and definitions1. Machine Learning and Deep Learning2. Artificial Neural Networks3. Data Mining and Data SciencePart II. Artificial Intelligence. deep learning and generative AI4. Transformers5. Bidirectional Encoder Representations from Transformers (BERT)6. Generative AI, Large Language Models7. GPT. Generative Pre-trained Transformers8. BARDPart III. Artificial Intelligence in Biomedical Research9. Bioinformatics methods and AI.10. Network Science methods and AI11. AI for investigating the molecular basis of diseases.12. AI and Drug RepurposingPart IV. Artificial Intelligence in Clinical Practice13. AI based analysis of biosignals14. AI-based analysis of bioimages15. AI-based analysis of Medical Reports and Electronic Health Records16. AI in surgery17. AI in oncologyPart V. Artificial Intelligence in Public Health18. One-Health AI19. Virus diffusion prevention and managementPart VI. 20. Opportunities and Risks of Generative AI (GPT) in Medicine21. Bias22. Clinician and Dataset Shift23. Explainability and Black Box models24. Privacy and Security25. Legal and ethical aspects26. Integrating human and AI knowledge