Artificial Intelligence in dentistry

This richly illustrated book offers a deeper understanding of the foundational concepts of AI, its practical applications in oral health, and the possibilities that lie ahead. From oral pathology to maxillofacial surgery, prosthodontics to orthodontics, and endodontics to dental education, it presents compelling, evidence-based insights into how AI is changing the landscape of dentistry. Beyond its clinical potential, the book tackles the key risks and challenges associated with AI implementation. It provides a thoughtful roadmap for addressing ethical considerations, encouraging transparency, and developing solutions that prioritize both innovation and patient well-being.

Over 19 chapters in this comprehensive book readers will learn about AI-supported pathways for the diagnosis and treatment of dental caries, periodontal bone loss, impacted teeth, periapical lesions, crown, and root fractures, working length determination, and detecting root and canal morphology, TMJ disorders, detection of obstructive sleep apnea, oral mucosal lesions, and many more. Critical information on applications of AI in the field of Oral and Maxillofacial Radiology, Implants, Endodontics, Prosthodontics, Restorative dentistry, Oral surgery, Periodontics, and Orthodontics. The book explains the advantages, disadvantages, and limitations of AI in dental health and delves into the medico-legal aspects of AI.

This book provides information on digital aspects in all dental fields including digital caries detection systems, digital colour matching, and digital applications in periodontology, surgical implant placement, oral histopathology and paediatric dentistry. This book contains detailed digital procedures, their basics and their applications, as well as providing information on Artificial Intelligence in dentistry, tissue engineering applications and dental education tools in digital dentistry.

This book covers the application of emerging technologies, occurring after the 4th industrial revolution, in oral and maxillofacial surgery (OMFS) and introduces a new era of personalized medicine in this discipline. It describes the manufacturing and data acquisition methods, including the advantages and disadvantages of each process. The workflow of using the emerging technologies in reconstructive treatments, orthognathic surgery, implant dentistry, robotic surgery and bio-fabrication are covered, including case study examples. Several chapters cover the use of artificial intelligence in this field.

This book is a practical guide for dental students and clinicians to understand and apply generative AI in practice—without needing programming skills. It covers essential AI concepts like natural language processing and Retrieval-Augmented Generation, then moves into hands-on strategies for prompt engineering, stakeholder engagement, error management, and integrating AI into clinical workflows.
Through real-world exercises and an “AI Journal Club,” readers learn to use AI safely in patient care, documentation, and quality improvement. Later chapters explore ethics, research, collaboration, and career development in digital dentistry. A valuable resource for those looking to confidently incorporate AI into their dental careers.

This book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. The book includes up-to-date information on different machine learning tools and their applicability in various dental specialties. A selection of examples illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges.

This book explores the applications of cutting-edge technologies in healthcare. The content combines theoretical analysis and medical application across several innovative methods, including an AI-based computer-aided diagnosis system, a blockchain-based AI system framework for healthcare, pre-processing algorithms for medical imaging, digital twin models for healthcare, a healthcare platform based on cloud, fog, and edge computing, and a personal health device domain information model.

This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks.

This book discusses applications of artificial intelligence in anaesthesiology, including control of anesthesia, risk prediction, ultrasound guidance, pain management, and operating room logistics.It makes practical recommendations for AI technology in anesthesiology as well as covering challenges and problems faced through the use of artificial intelligence in anesthesiology..

This book covers the principles, concepts, and applications of artificial intelligence in medical imaging technologies, specifically in the context of diagnostic imaging, such as radiography and radiological technology. First, artificial intelligence and its subsets machine learning and deep learning are described followed by a discussion of applications of these AI principles in medical imaging technologies. Finally, ethical questions, regulatory aspects, and future trends and challenges are also reviewed in this textbook.

This book provides a solid foundation to understand Artificial Intelligence (AI) and its growing role in healthcare. With the rise of generative AI tools like ChatGPT, clinical practice, education, and research are rapidly evolving.
Covering key topics such as algorithms, machine learning, large language models, and natural language processing, the book also explores ethical, legal, and regulatory considerations.

This open access collection of AI ethics case studies presents real-life case studies combined with commentaries and strategies for overcoming ethical challenges.

This book is a practical guide for dental students and clinicians to understand and apply generative AI in practice—without needing programming skills. It covers essential AI concepts like natural language processing and Retrieval-Augmented Generation, then moves into hands-on strategies for prompt engineering, stakeholder engagement, error management, and integrating AI into clinical workflows.
Through real-world exercises and an “AI Journal Club,” readers learn to use AI safely in patient care, documentation, and quality improvement. Later chapters explore ethics, research, collaboration, and career development in digital dentistry. A valuable resource for those looking to confidently incorporate AI into their dental careers.

This book aims to provide physicians and scientists with the basics of Artificial Intelligence (AI) with a special focus on medical imaging. The contents of the book provide an introduction to the main topics of artificial intelligence currently applied on medical image analysis.