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Full Description
Revolutionizing Healthcare: The Role of Machine Learning and Artificial Intelligence describes the complexity of healthcare data that necessitates the expanding use of artificial intelligence (AI). This book offers an explicit accounting of vital aspects on artificial intelligence in healthcare, discussing perspectives of the technologies explored based on findings outlined in highly organized tables, illustrative figures, and flow charts. It brings together novel applications of artificial intelligence in healthcare and helps readers define major gaps in knowledge that can lead to significant scientific discoveries.
In addition, the book covers computational drug design, genomic data mining, nanomedicines, medical devices, cosmeceuticals, biosensors, genome counseling, quality control, clinical trials, and cybersecurity. Researchers, students, and scientists will find the book provides foundational and practical knowledge, along with the most advanced AI applications in healthcare.
Contents
1. History and introduction of machine learning and artificial intelligence
2. Current landscape of machine learning and artificial intelligence in healthcare
3. Rise of artificial intelligence in modern healthcare and pharmaceutical industry
4. Advances in computational drug design and drug discovery: Integrating artificial intelligence and molecular modelling
5. Artificial intelligence-driven genomic data mining for biomarker discovery and therapeutic target identification
6. Artificial intelligence driven predictive modelling for disease progression and prognosis
7. Artificial intelligence powered drug delivery system
8. Artificial intelligence-driven innovations in nanomedicines
9. Harnessing artificial intelligence for innovative medical devices
10. Artificial intelligence innovation in skin health and cosmeceuticals
11. Cognitive biosensing: Harnessing artificial intelligence for biosensors
12. Artificial intelligence in personalised medicine and genome counselling
13. Artificial intelligence driven automation in quality control and assurance in pharmaceutical manufacturing
14. Artificial intelligence and digitalisation in regulatory science
15. Integrating artificial intelligence in clinical trials
16. Cybersecurity Risks in artificial intelligence enabled healthcare: Safeguarding patient data
17. Ethical algorithms: Navigating the moral landscape and impact of AI in healthcare, addressing bias, privacy and equity
18. Limitations and future of artificial intelligence in healthcare
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