The Role of Machine Learning and Artificial Intelligence in Revolutionizing Healthcare
- 1st Edition - January 1, 2027
- Latest edition
- Editors: Prashant Kesharwani, M. Afshar Alam
- Language: English
Revolutionizing Healthcare: The Role of Machine Learning and Artificial Intelligence describes the complexity of healthcare data that necessitates the expanding use of artifi… Read more
Description
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.
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.
Key features
Key features
- Presents a consistent and thorough overview of artificial intelligence in healthcare, focusing on foundational concepts and wide applications
- Offers an explicit accounting of vital aspects of artificial intelligence in healthcare, discussing technological perspectives based on findings outlined in organized tables, illustrative figures, and flow charts
- Encourages multidisciplinary collaboration to tackle key challenges in AI technology within healthcare, fostering innovation and advancements
Readership
Readership
Post graduate students and researchers in IT and computer science working in healthcare and pharmaceutical related disciplines.
Table of contents
Table of 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
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
Product details
Product details
- Edition: 1
- Latest edition
- Published: January 1, 2027
- Language: English
About the editors
About the editors
PK
Prashant Kesharwani
Dr. Prashant Kesharwani is an Assistant Professor of Pharmaceutics at Dr. Harisingh Gour Vishwavidyalaya (A Central University), Sagar, India. His work focuses on translational nanomedicine, polymeric biomaterials, targeted drug delivery, nanoengineered drug delivery systems, and translational pharmaceutical research. He has contributed extensively to the scientific literature and has served as an editor of scholarly books. Dr. Kesharwani has received research funding from national agencies and has been recognized with awards and fellowships for his contributions to the field. His research interests include nanomedicine, targeted and stimuli-responsive drug delivery, polymeric nanocarriers, and related pharmaceutical applications. He is actively involved in scientific research, academic mentoring, and scholarly publishing.
Affiliations and expertise
Dr. Harisingh Gour Vishwavidyalaya University, IndiaMA
M. Afshar Alam
M. Afshar Alam was appointed Vice-Chancellor of Jamia Hamdard in 2021. He has held several academic and leadership positions at the university, including Head of the Department of Computer Science and dean-level positions in management, information technology, engineering, science, and technology. His research interests include software re-engineering, data mining, and sustainable development. He has authored books and published extensively in academic journals and has served on committees associated with several Government of India educational and research bodies, including the University Grants Commission (UGC), All India Council of Technical Education (AICTE), and Science Engineering and Research Board (SERB). He has also received a number of awards for his contributions to education and research.
Affiliations and expertise
Former Vice-Chancellor and Professor, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India