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 (AI) 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 Artificial Intelligence in Healthcare: Trends, Applications, and Future Directions is structured into several parts, each addressing crucial aspects of AI in healthcare. It first…mehr
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 (AI) 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 Artificial Intelligence in Healthcare: Trends, Applications, and Future Directions is structured into several parts, each addressing crucial aspects of AI in healthcare. It first discusses the challenges and future scope of AI in healthcare systems and goes on to review the mathematical foundations and big data that form the basis of AI applications. The subsequent parts cover data processing and collection, AI application in diagnosis and treatment, imaging and disease detection, robotics, automation, pharmaceutical and biomedical applications, ethical considerations, and future trends and directions. The diverse range of topics covered reflects the complexity and richness of this field, providing readers with a well-rounded perspective on the subject matter. Designed to bridge the gap between the technical intricacies of AI and the real-world implications for healthcare professionals, researchers, and policymakers, this book provides readers with a multidimensional understanding of how AI is transforming healthcare, shaping the present, and guiding the future of medical practices. The book will serve as a catalyst for further exploration, collaboration, and innovation in leveraging AI for the betterment of healthcare practices worldwide.
Sakshi Gupta, PhD, is a dedicated and diligent educator, working as an Associate Professor in the Department of Mathematics, Applied Sciences and Humanities at the Dronacharya College of Engineering, Gurugram, Haryana, India. Prior to this, she has worked at SGT University Gurugram, Haryana; Amity University, Gurugram, Haryana; The NorthCap University, Gurugram, Haryana; and Government College, Chandigarh, India. She has over nine years of experience in research and academics. Her research interests include computational modeling and analysis, graph theory, and petri nets. She has published eight research papers and book chapters in peer-reviewed reputed international journals and Springer international conferences (SCI, Scopus, WOS). She has attended more than 25 faculty development programs, seminars, and workshops. She presented her research work R various national and international conferences. She has also received a best paper award from Jawaharlal Nehru University, New Delhi. She completed her MSc in Mathematics & Computing from Thapar University, Patiala, India. Dr. Sakshi earned her PhD degree in Mathematics with a specialization in Graph Theory from Amity University Gurugram, Haryana. She has qualified Joint CSIR-UGC NET Exam, December 2009 in Mathematics with AIR 23. She is also skilled in LaTex (technical writing software). Aryan Chaudhary is the Chief Scientific Advisor at BioTech Sphere Research, India, Aryan continues to make groundbreaking contributions to the industry. Having served as the Research Head at Nijji HealthCare Pvt Ltd, he has demonstrated his expertise in leveraging revolutionary technologies such as artificial intelligence, deep learning, IoT, cognitive technology, and blockchain to revolutionize the healthcare landscape. His relentless pursuit of excellence and innovation has earned him recognition as a thought leader in the industry. His dedication to advancing healthcare is evident through his vast body of work. He has authored several influential academic papers on public health and digital health, published in prestigious international journals. His research primarily focuses on integrating IoT and sensor technology for efficient data collection through one-time and ambulatory monitoring. As a testament to his expertise and leadership, he is not only a keynote speaker at numerous international and national conferences but also serves as the Series Editor of a CRC book series and is the editor of several books on biomedical science. His commitment to the advancement of scientific knowledge extends further, as he acts as a guest editor for special issues in renowned journals. Recognized for his significant contributions, he has received prestigious accolades, including 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. Moreover, he holds senior memberships in various international science associations, reflecting his influence and impact in the field. Adding to his accomplishments, Aryan Chaudhary is currently serving as a guest editor for a special issue in the highly-regarded journal, EAI Endorsed Transactions on AI and Robotics, and he has joined the editorial board of Biomedical Science and Clinical Research (BSCR). Additionally, he is a respected professional member of the Association for Computing Machinery (ACM).
Inhaltsangabe
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 of Lensing Safety and Big Data Protection 2. Review of the 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 an 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 Scans 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. Revolutionizing Healthcare Using Metaverse Virtual Worlds and Augmented Reality Bentonite 16. Robotics and Automation in Healthcare PART VI: PHARMACEUTICAL AND BIOMEDICAL APPLICATIONS 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 Dilemmas in AI: The Essential Evil to Be Dealt With PART VIII: FUTURE TRENDS AND DIRECTION 21. Rise of 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 Artificial Intelligences in Healthcare
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 of Lensing Safety and Big Data Protection 2. Review of the 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 an 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 Scans 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. Revolutionizing Healthcare Using Metaverse Virtual Worlds and Augmented Reality Bentonite 16. Robotics and Automation in Healthcare PART VI: PHARMACEUTICAL AND BIOMEDICAL APPLICATIONS 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 Dilemmas in AI: The Essential Evil to Be Dealt With PART VIII: FUTURE TRENDS AND DIRECTION 21. Rise of 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 Artificial Intelligences in Healthcare
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