Artificial Intelligence in Healthcare (eBook, ePUB)
Trends, Applications, and Future Directions
Redaktion: Gupta, Sakshi; Chaudhary, Aryan
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Artificial Intelligence in Healthcare (eBook, ePUB)
Trends, Applications, and Future Directions
Redaktion: Gupta, Sakshi; Chaudhary, Aryan
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This comprehensive book brings together a diverse collection of insights from experts in medicine, computer science, and data analytics to explore the evolving role of artificial intelligence in the healthcare sector. The chapters delve into various facets of AI applications, from legal considerations and mathematical foundations to the practical implementations of machine learning and deep learning in healthcare.
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This comprehensive book brings together a diverse collection of insights from experts in medicine, computer science, and data analytics to explore the evolving role of artificial intelligence in the healthcare sector. The chapters delve into various facets of AI applications, from legal considerations and mathematical foundations to the practical implementations of machine learning and deep learning in healthcare.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 498
- Erscheinungstermin: 12. Februar 2026
- Englisch
- ISBN-13: 9781040875872
- Artikelnr.: 76223046
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 498
- Erscheinungstermin: 12. Februar 2026
- Englisch
- ISBN-13: 9781040875872
- Artikelnr.: 76223046
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Sakshi Gupta, PhD, is an Associate Professor of Mathematics, Applied Sciences and Humanities at the Dronacharya College of Engineering, India. She has research experience in modeling and dynamic analysis of complex networks in interdisciplinary fields using computational and applied mathematical techniques. She has published research papers and book chapters and has attended many faculty development programs, seminars, and workshops. She has presented her research work at national and international conferences. Prof. Gupta holds a PhD degree in Mathematics with a specialization in Graph Theory from Amity University Gurugram, Haryana, India. Aryan Chaudhary is the Chief Scientific Advisor at BioTech Sphere Research, India. He was previously the Research Head at Nijji HealthCare Pvt Ltd. He has authored several influential academic papers on public health and digital health and has been a keynote speaker at numerous international and national conferences. He is also a book series editor and editor of several books on biomedical science. Recognized for his contributions, he has received prestigious accolades, including being named the "Most Inspiring Young Leader in Healthtech Space 2022" by Business Connect and the title of the best project leader at Global Education and Corporate Leadership.
Foreword by Isha Malhotra Preface PART I: INTRODUCTION TO AI IN HEALTHCARE
1. Conundrums in Application of Artificial Intelligence (AI) in Modern
Healthcare Systems: Legal Admissibility, Challenges, and Future Scope
Lensing Safety, and Big Data Protection 2. Review on Role of Mathematical
Foundations of AI in Healthcare PART II: DATA PROCESSING AND COLLECTION IN
HEALTHCARE 3. Big Data Analytics in the Healthcare Sector PART III: AI
APPLICATION IN DIAGNOSIS AND TREATMENT 4. Machine Learning Algorithms for
Healthcare: Applications, Analysis, and Future Directions 5. Insights in
Contemporary Machine Learning Approaches in the Diagnosis and Treatment of
Migraines 6. Artificial Intelligence-Driven Diagnostic Systems 7. Exploring
the Level of Students Mental Health Anxiety Utilizing the Application of
Artificial Intelligence Algorithm PART IV: IMAGING AND DISEASE DETECTION
8. Deep Learning in Medical Imaging 9. Exploring Deep Learning Models for
COVID-19 Detection from CT Scan and X-Ray Images 10. Using Machine Learning
Techniques to Detect COVID-19, Pneumonia, and Tuberculosis (TB) Based on
Analysis for Chest X-Ray Images 11. Skin Cancer Detection Based on Color
and Texture Feature-Based Extraction 12. Deep Learning Approach for
Glioblastoma Brain Tumor Classification and Prevention 13. Multi-Label
Machine Learning Techniques with Stacking CV Classifiers for the Optimal
Medical Diagnosis of Cardiovascular Diseases PART V: ROBOTICS, AUTOMATION,
AND VIRTUAL WORLDS IN HEALTHCARE 14. Enhanced Chatbot Assistance for
Patient Healthcare 15. Revolutionize Healthcare Using Metaverse Virtual
Worlds and Augmented Reality Bentonite 16. Robotics and Automation in
Healthcare PART VI: PHARMACEUTICAL AND BIOMEDICAL APPLICATION 17. AI in
Drug Discovery and Development 18. The Emergence of Artificial Intelligence
(AI) in Pharmaceutical and Biomedical Sciences PART VII: ETHICAL
CONSIDERATIONS AND CHALLENGES 19. Transformative Advances and Ethical
Considerations in AI-Driven Healthcare: A Comprehensive Exploration of
Emerging Trends 20. Ethical Dilemma With AI: The Essential Evil to Be Dealt
With PART VIII: FUTURE TRENDS AND DIRECTION 21. Rise in AI: A
Transformative Tool in Emerging Trends in the Healthcare Sector 22.
Navigating the Future: Collaborative AI-Human Dynamics in Rehabilitation
23. Emerging Trends in Healthcare Artificial Intelligence
1. Conundrums in Application of Artificial Intelligence (AI) in Modern
Healthcare Systems: Legal Admissibility, Challenges, and Future Scope
Lensing Safety, and Big Data Protection 2. Review on Role of Mathematical
Foundations of AI in Healthcare PART II: DATA PROCESSING AND COLLECTION IN
HEALTHCARE 3. Big Data Analytics in the Healthcare Sector PART III: AI
APPLICATION IN DIAGNOSIS AND TREATMENT 4. Machine Learning Algorithms for
Healthcare: Applications, Analysis, and Future Directions 5. Insights in
Contemporary Machine Learning Approaches in the Diagnosis and Treatment of
Migraines 6. Artificial Intelligence-Driven Diagnostic Systems 7. Exploring
the Level of Students Mental Health Anxiety Utilizing the Application of
Artificial Intelligence Algorithm PART IV: IMAGING AND DISEASE DETECTION
8. Deep Learning in Medical Imaging 9. Exploring Deep Learning Models for
COVID-19 Detection from CT Scan and X-Ray Images 10. Using Machine Learning
Techniques to Detect COVID-19, Pneumonia, and Tuberculosis (TB) Based on
Analysis for Chest X-Ray Images 11. Skin Cancer Detection Based on Color
and Texture Feature-Based Extraction 12. Deep Learning Approach for
Glioblastoma Brain Tumor Classification and Prevention 13. Multi-Label
Machine Learning Techniques with Stacking CV Classifiers for the Optimal
Medical Diagnosis of Cardiovascular Diseases PART V: ROBOTICS, AUTOMATION,
AND VIRTUAL WORLDS IN HEALTHCARE 14. Enhanced Chatbot Assistance for
Patient Healthcare 15. Revolutionize Healthcare Using Metaverse Virtual
Worlds and Augmented Reality Bentonite 16. Robotics and Automation in
Healthcare PART VI: PHARMACEUTICAL AND BIOMEDICAL APPLICATION 17. AI in
Drug Discovery and Development 18. The Emergence of Artificial Intelligence
(AI) in Pharmaceutical and Biomedical Sciences PART VII: ETHICAL
CONSIDERATIONS AND CHALLENGES 19. Transformative Advances and Ethical
Considerations in AI-Driven Healthcare: A Comprehensive Exploration of
Emerging Trends 20. Ethical Dilemma With AI: The Essential Evil to Be Dealt
With PART VIII: FUTURE TRENDS AND DIRECTION 21. Rise in AI: A
Transformative Tool in Emerging Trends in the Healthcare Sector 22.
Navigating the Future: Collaborative AI-Human Dynamics in Rehabilitation
23. Emerging Trends in Healthcare Artificial Intelligence
Foreword by Isha Malhotra Preface PART I: INTRODUCTION TO AI IN HEALTHCARE
1. Conundrums in Application of Artificial Intelligence (AI) in Modern
Healthcare Systems: Legal Admissibility, Challenges, and Future Scope
Lensing Safety, and Big Data Protection 2. Review on Role of Mathematical
Foundations of AI in Healthcare PART II: DATA PROCESSING AND COLLECTION IN
HEALTHCARE 3. Big Data Analytics in the Healthcare Sector PART III: AI
APPLICATION IN DIAGNOSIS AND TREATMENT 4. Machine Learning Algorithms for
Healthcare: Applications, Analysis, and Future Directions 5. Insights in
Contemporary Machine Learning Approaches in the Diagnosis and Treatment of
Migraines 6. Artificial Intelligence-Driven Diagnostic Systems 7. Exploring
the Level of Students Mental Health Anxiety Utilizing the Application of
Artificial Intelligence Algorithm PART IV: IMAGING AND DISEASE DETECTION
8. Deep Learning in Medical Imaging 9. Exploring Deep Learning Models for
COVID-19 Detection from CT Scan and X-Ray Images 10. Using Machine Learning
Techniques to Detect COVID-19, Pneumonia, and Tuberculosis (TB) Based on
Analysis for Chest X-Ray Images 11. Skin Cancer Detection Based on Color
and Texture Feature-Based Extraction 12. Deep Learning Approach for
Glioblastoma Brain Tumor Classification and Prevention 13. Multi-Label
Machine Learning Techniques with Stacking CV Classifiers for the Optimal
Medical Diagnosis of Cardiovascular Diseases PART V: ROBOTICS, AUTOMATION,
AND VIRTUAL WORLDS IN HEALTHCARE 14. Enhanced Chatbot Assistance for
Patient Healthcare 15. Revolutionize Healthcare Using Metaverse Virtual
Worlds and Augmented Reality Bentonite 16. Robotics and Automation in
Healthcare PART VI: PHARMACEUTICAL AND BIOMEDICAL APPLICATION 17. AI in
Drug Discovery and Development 18. The Emergence of Artificial Intelligence
(AI) in Pharmaceutical and Biomedical Sciences PART VII: ETHICAL
CONSIDERATIONS AND CHALLENGES 19. Transformative Advances and Ethical
Considerations in AI-Driven Healthcare: A Comprehensive Exploration of
Emerging Trends 20. Ethical Dilemma With AI: The Essential Evil to Be Dealt
With PART VIII: FUTURE TRENDS AND DIRECTION 21. Rise in AI: A
Transformative Tool in Emerging Trends in the Healthcare Sector 22.
Navigating the Future: Collaborative AI-Human Dynamics in Rehabilitation
23. Emerging Trends in Healthcare Artificial Intelligence
1. Conundrums in Application of Artificial Intelligence (AI) in Modern
Healthcare Systems: Legal Admissibility, Challenges, and Future Scope
Lensing Safety, and Big Data Protection 2. Review on Role of Mathematical
Foundations of AI in Healthcare PART II: DATA PROCESSING AND COLLECTION IN
HEALTHCARE 3. Big Data Analytics in the Healthcare Sector PART III: AI
APPLICATION IN DIAGNOSIS AND TREATMENT 4. Machine Learning Algorithms for
Healthcare: Applications, Analysis, and Future Directions 5. Insights in
Contemporary Machine Learning Approaches in the Diagnosis and Treatment of
Migraines 6. Artificial Intelligence-Driven Diagnostic Systems 7. Exploring
the Level of Students Mental Health Anxiety Utilizing the Application of
Artificial Intelligence Algorithm PART IV: IMAGING AND DISEASE DETECTION
8. Deep Learning in Medical Imaging 9. Exploring Deep Learning Models for
COVID-19 Detection from CT Scan and X-Ray Images 10. Using Machine Learning
Techniques to Detect COVID-19, Pneumonia, and Tuberculosis (TB) Based on
Analysis for Chest X-Ray Images 11. Skin Cancer Detection Based on Color
and Texture Feature-Based Extraction 12. Deep Learning Approach for
Glioblastoma Brain Tumor Classification and Prevention 13. Multi-Label
Machine Learning Techniques with Stacking CV Classifiers for the Optimal
Medical Diagnosis of Cardiovascular Diseases PART V: ROBOTICS, AUTOMATION,
AND VIRTUAL WORLDS IN HEALTHCARE 14. Enhanced Chatbot Assistance for
Patient Healthcare 15. Revolutionize Healthcare Using Metaverse Virtual
Worlds and Augmented Reality Bentonite 16. Robotics and Automation in
Healthcare PART VI: PHARMACEUTICAL AND BIOMEDICAL APPLICATION 17. AI in
Drug Discovery and Development 18. The Emergence of Artificial Intelligence
(AI) in Pharmaceutical and Biomedical Sciences PART VII: ETHICAL
CONSIDERATIONS AND CHALLENGES 19. Transformative Advances and Ethical
Considerations in AI-Driven Healthcare: A Comprehensive Exploration of
Emerging Trends 20. Ethical Dilemma With AI: The Essential Evil to Be Dealt
With PART VIII: FUTURE TRENDS AND DIRECTION 21. Rise in AI: A
Transformative Tool in Emerging Trends in the Healthcare Sector 22.
Navigating the Future: Collaborative AI-Human Dynamics in Rehabilitation
23. Emerging Trends in Healthcare Artificial Intelligence







