Artificial Intelligence in Medicine and Dentistry

Advancing Science, Education, and Clinical Practice
Erscheinungsjahr 2026
ISBN: 978-3-032-15976-2
Verlag: Springer

Buch, Englisch, 269 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 604 g

This comprehensive book bridges the gap between cutting-edge artificial intelligence (AI) technology and its practical applications in dentistry and medicine. It empowers healthcare professionals, educators, and students to stay ahead in a rapidly evolving field by providing in-depth knowledge and practical insights into how AI is transforming diagnostics, treatment planning, patient care, and education. The book thoroughly explores AI-driven innovations, such as enhanced dental diagnostics, robotics in surgery, personalized medicine, and the integration of AI into medical and dental education. Packed with real-world examples and case studies, it offers actionable strategies for implementing AI tools and technologies in clinical practice. Readers will gain a deep understanding of the ethical considerations and legal frameworks essential for the responsible adoption of AI, ensuring they are well-equipped to navigate the complexities of modern healthcare.  

is designed to help professionals elevate their practice, improve patient outcomes, and contribute to the advancement of healthcare. It serves as a vital resource for anyone looking to harness the power of AI to revolutionize their field, fostering innovation and driving progress in dentistry and medicine.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Tayebi, Lobat

Shetty, Sachin

Imani, Seyedmisagh

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Zahnmedizin
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Ethik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Biomedizin, Medizinische Forschung, Klinische Studien

Inhaltsverzeichnis

Introduction of Artificial Intelligence in Healthcare.- Part I: AI in Medicine.- AI in Medical Diagnostics.- AI in Treatment and Patient Care.- AI in Medical Education.- AI in Healthcare Management.- Part II: AI in Dentistry.- AI in Dental Diagnostics.- AI in Dental Treatment Planning.- AI in Dental Education.- AI in Dental School and Practice Management.- AI Research in Medicine and Dentistry.- The Future of AI in Healthcare Education and Science.

Über Autor(innen)

Lobat Tayebi, PhD, DPhil, is the Batten Endowed Professor in the Department of Electrical and Computer Engineering at Old Dominion University (ODU), where she serves as the director of the Institute for Engineering in Medicine, Health & Human Performance (EnMed). Dr. Tayebi joined ODU after nearly a decade at Marquette University School of Dentistry, where she was a Professor and Director of Research. She earned a PhD from the University of California-Davis in Applied Science and a DPhil degree from the University of Oxford in Engineering Science, Institute of Biomedical Engineering. Her expertise lies in tissue engineering and regenerative medicine. Dr. Tayebi's publications, patents, and presentations comprise six published patents, over 400 articles (h-index: 78), including papers in Nature Materials and Advanced Materials, and over 200 conference presentations and proceedings. She is the author of the books Research Methods in Dentistry (Springer, 2022) and 3D Printing in Oral and Maxillofacial Surgery (Springer, 2021). In addition, she is the editor of the books Application of Biomedical Engineering in Dentistry (Springer, 2019) and Biomaterials for Oral and Dental Tissue Engineering (Elsevier, 2017), which was selected as one of the 20 Best Biomaterials Books of All Time by BookAuthority. She is the recipient of the "President's Cup for Creative Interdisciplinarity (2014, Oklahoma State University) and "Rising Star, 2016" (Marquette University). She enjoys interdisciplinary projects and genuinely believes in the effectiveness of multidisciplinary efforts.
 
Sachin Shetty, PhD, is an Executive Director of the Center for Secure and Intelligent Critical Systems at the Virginia Modeling, Analysis, and Simulation Center and holds a joint appointment as a Professor with the Department of Electrical and Computer Engineering at Old Dominion University. His research interests lie at the intersection of computer networking, network security, and machine learning. Over the past 15 years, Dr. Shetty has completed many large-scale projects with multiple collaborators and institutions and served as the PI/Co-PI on various grants and contracts funded by numerous military and federal government departments and private businesses. He is the Technical Lead for the 5G Network Enhancement Prototype at Marine Corps Logistics Base, Albany, Georgia. Dr. Shetty has published over 200 research articles in journals and conference proceedings and edited four books. Two of his research papers were selected as the Top 50 academic papers in Blockchain in 2018. He is a Commonwealth Cyber Initiative Fellow, a recipient of the DHS Scientific Leadership Award, participated in the Fulbright Specialist Program, and was inducted into the Tennessee State University Million Dollar Club. Dr. Shetty won the Electric Power Research Institute (EPRI) Cyber Security Research Challenge in 2019. He is a Senior Member of the IEEE.
 
Seyedmisagh Imani, PhD,  is a Postdoctoral Research Scholar at Old Dominion University, specializing in artificial intelligence, biomechanics, tissue engineering, and biomaterials. He focuses on enhancing patient care in medicine and dentistry through innovative technological solutions. Dr. Imani is currently developing AI-driven models to predict oral health outcomes, optimize treatment planning, and identify risk factors associated with dental conditions. He held a Research Fellowship at Massachusetts General Hospital, Harvard Medical School, where he investigated the relationship between aging, age-related diseases, and joint replacement using machine learning algorithms. An active contributor to the scientific community, he has authored numerous peer-reviewed articles and holds several patents in the biomedical field. He is dedicated to advancing medical and dental sciences through multidisciplinary research and innovation.