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Machine Learning in Dentistry

2021-07-24 Medical
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Release : 2021-07-24
Genre : Medical
Kind : eBook
Book Rating : 816/5 ( reviews)

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Book Synopsis Machine Learning in Dentistry by : Ching-Chang Ko

Download or read book Machine Learning in Dentistry written by Ching-Chang Ko. This book was released on 2021-07-24. Available in PDF, EPUB and Kindle. Book excerpt: 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. Machine learning is an emerging field of artificial intelligence research and practice in which computer agents are employed to improve perception, cognition, and action based on their ability to “learn”, for example through use of big data techniques. Its application within dentistry is designed to promote personalized and precision patient care, with enhancement of diagnosis and treatment planning. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties. The selected examples amply illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges. Machine Learning in Dentistry will be of value for all dental practitioners and researchers who wish to learn more about the potential benefits of using machine learning techniques in their work.

Artificial Intelligence in Dentistry

2024-02-11 Medical
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Release : 2024-02-11
Genre : Medical
Kind : eBook
Book Rating : 272/5 ( reviews)

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Book Synopsis Artificial Intelligence in Dentistry by : Kaan Orhan

Download or read book Artificial Intelligence in Dentistry written by Kaan Orhan. This book was released on 2024-02-11. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive book focuses on various aspects of artificial intelligence in dentistry, assisting dentists, specialists, and scientists in advancing their understanding, knowledge, training, and expertise in this field of artificial intelligence. 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. Prediction tasks include the estimation of retreatment needs and third molar eruption. Critical information on applications of AI in the field of Oral and Maxillofacial Radiology, Implants, Endodontics, Prosthodontics, Restorative dentistry, Oral surgery, Periodontics, and Orthodontics. Gain valuable insight into studies applying machine learning based on Machine Learning (ML), Deep Learning (DL), and Artificial Neural Networks (ANN). Explore the technical aspects and medical applications of AI in dentistry. Additionally, discover cutting-edge topics like 3D and bioprinting applications of AI and its integration into dental education. All the chapters provide thorough, evidence-based data on AI and its implications in oral health, bridging the gap between knowledge and practical application. The book explains the advantages, disadvantages, and limitations of AI in dental health. Delve into the medico-legal aspects of AI to navigate this cutting-edge landscape responsibly. Learn about applications of Machine Learning and Artificial Intelligence in the Covid-19 Pandemic. Extensive information on deep learning in image processing, including various types of neural networks, image segmentation, enhancement, reconstruction, and registration. This book concludes with an exploration of AI's exciting potential and future perspectives in the dental field, paving the way for a new era of oral healthcare. Don't miss out on this unique resource for AI in Dentistry, which empowers you to stay at the forefront of innovation and embrace the AI revolution in Dentistry. Be prepared for the future of dentistry.

Artificial Intelligence in Dentistry

2022-12-05 Technology & Engineering
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Release : 2022-12-05
Genre : Technology & Engineering
Kind : eBook
Book Rating : 151/5 ( reviews)

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Book Synopsis Artificial Intelligence in Dentistry by : Khalid Shaikh

Download or read book Artificial Intelligence in Dentistry written by Khalid Shaikh. This book was released on 2022-12-05. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to next-generation applications and technologies for improving diagnostic accuracy and prediction of treatment outcomes in dentistry through the use of artificial intelligence (AI) and machine learning (ML). The authors attempt to bridge the gap between dental research and global health outcomes, as well as provide a comprehensive guide to general and clinical aspects of dental and oral health issues and the etiology, prevalence, assessment, and management of these conditions. This book combines engineering applications and medical healthcare and will be an important reference for researchers, biomedical engineers, dental students, and dental practitioners.

Role of Artificial Intelligence in Dentistry: Current applications and future perspectives

2024-05-14 Antiques & Collectibles
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Release : 2024-05-14
Genre : Antiques & Collectibles
Kind : eBook
Book Rating : 771/5 ( reviews)

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Book Synopsis Role of Artificial Intelligence in Dentistry: Current applications and future perspectives by : Dr Seema Jabeen

Download or read book Role of Artificial Intelligence in Dentistry: Current applications and future perspectives written by Dr Seema Jabeen. This book was released on 2024-05-14. Available in PDF, EPUB and Kindle. Book excerpt: In the past few years, artificial intelligence (AI) has received enormous attention and it has evolved to being one of the main drivers of not only modern life, through Siri, Alexa, using Google, etc. but also medicine. Throughout business, AI and associated innovations are increasingly widespread and are starting to be applied to the healthcare. [1] These technologies are capable of changing many aspects of healthcare, as well as administrative structures within hospitals, payers and pharmaceutical organizations. Although it is a new technology, AI has been increasingly utilized in different medical specialties to diagnose conditions, interpret results, and help healthcare providers to achieve good treatment outcomes.

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

2019-09-10 Computers
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Release : 2019-09-10
Genre : Computers
Kind : eBook
Book Rating : 540/5 ( reviews)

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Book Synopsis Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by : Wojciech Samek

Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek. This book was released on 2019-09-10. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.

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