Machine Learning In Dentistry
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Machine Learning In Dentistry
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Author : Ching-Chang Ko
language : en
Publisher: Springer Nature
Release Date : 2021-07-24
Machine Learning In Dentistry written by Ching-Chang Ko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-24 with Medical categories.
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
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Author : Kaan Orhan
language : en
Publisher: Springer Nature
Release Date : 2024-01-10
Artificial Intelligence In Dentistry written by Kaan Orhan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-10 with Medical categories.
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), DeepLearning (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 And Machine Learning In 2d 3d Medical Image Processing
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Author : Rohit Raja
language : en
Publisher: CRC Press
Release Date : 2020-12-23
Artificial Intelligence And Machine Learning In 2d 3d Medical Image Processing written by Rohit Raja and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-23 with Technology & Engineering categories.
Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field
Machine Learning And Deep Learning Techniques For Medical Science
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Author : K. Gayathri Devi
language : en
Publisher: CRC Press
Release Date : 2022-05-11
Machine Learning And Deep Learning Techniques For Medical Science written by K. Gayathri Devi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-11 with Technology & Engineering categories.
The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).
Cancer Prediction For Industrial Iot 4 0
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Author : Meenu Gupta
language : en
Publisher: CRC Press
Release Date : 2021-12-30
Cancer Prediction For Industrial Iot 4 0 written by Meenu Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-30 with Health & Fitness categories.
Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines. Features • Covers the fundamentals, history, reality and challenges of cancer • Presents concepts and analysis of different cancers in humans • Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer • Offers real-world examples of cancer prediction • Reviews strategies and tools used in cancer prediction • Explores the future prospects in cancer prediction and treatment Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions. This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.
Machine Learning Optimization And Big Data
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Author : Panos M. Pardalos
language : en
Publisher: Springer
Release Date : 2016-12-24
Machine Learning Optimization And Big Data written by Panos M. Pardalos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-24 with Computers categories.
This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions. These proceedings contain papers in the fields of Machine Learning, Computational Optimization and DataScience presenting a substantial array of ideas, technologies, algorithms, methods and applications.
Digital Dentistry
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Author : Maher Ali Rusho
language : en
Publisher: Book Saga Publications
Release Date : 2024-05-18
Digital Dentistry written by Maher Ali Rusho and has been published by Book Saga Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-18 with Medical categories.
Dentistry is the practice of evaluating, diagnosing, preventing, and treating diseases, disorders, and conditions of the oral cavity, maxillofacial area, and related structures. This includes both nonsurgical and surgical procedures. Dentistry is provided by dentists who have received education, training, and experience in professional ethics and applicable laws. The field of pediatric dentistry has experienced a significant transformation due to the incorporation of cutting-edge technology and inventive medical instruments. Teledentistry has emerged as an effective and convenient approach for interacting with a wide variety of young patients. Teledentistry, in its contemporary understanding, encompasses the provision of teleconsultation support through online platforms, accessible at any time and from any place. This advancement provides a multitude of benefits that are particularly significant in the present healthcare setting, surpassing the traditional method of in-person dental treatment. Teledentistry offers a significant advantage in terms of increasing public knowledge about different oral health conditions and effectively conveying crucial information, particularly for children. Teledentistry effectively utilizes online media platforms to reach a wide and specific audience, particularly in emergencies where quick and comprehensive communication is vital. Within the field of pediatric dentistry, this implies that caregivers and parents can promptly obtain guidance and information, promoting improved oral hygiene practices for children and ensuring that vital information is readily accessible to address emerging dental problems in the younger population.
Leveraging Digital Technology For Preventive Dentistry
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Author : Asanza, Dachel Martínez
language : en
Publisher: IGI Global
Release Date : 2024-08-26
Leveraging Digital Technology For Preventive Dentistry written by Asanza, Dachel Martínez and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-26 with Medical categories.
Even in the modern age, oral diseases have a substantial and negative impact on citizens all over the globe. Oral diseases affect nearly half of the global population and represent a significant economic and health burden. As a result, the promotion of oral health and disease prevention information has emerged as one of the most cost-effective strategies in limiting these maladies and treating them should they occur. Leveraging Digital Technology for Preventive Dentistry provides relevant theoretical frameworks and the latest empirical research findings in the area. It discusses the latest findings in digital technologies for health promotion and oral disease promotion, as well as the behavior of these health actions in the international context. Covering topics such as ethical and legal aspects, preventive dentistry, and biometric studies, this book is an excellent resource for librarians, dentists, dental students and educators, researchers, academicians, and more.
Medical Risk Prediction Models
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Author : Thomas A. Gerds
language : en
Publisher: CRC Press
Release Date : 2021-02-01
Medical Risk Prediction Models written by Thomas A. Gerds and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-01 with Mathematics categories.
Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient’s individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest. Features: All you need to know to correctly make an online risk calculator from scratch Discrimination, calibration, and predictive performance with censored data and competing risks R-code and illustrative examples Interpretation of prediction performance via benchmarks Comparison and combination of rival modeling strategies via cross-validation Thomas A. Gerds is a professor at the Biostatistics Unit at the University of Copenhagen and is affiliated with the Danish Heart Foundation. He is the author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years. Michael W. Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service, and the John M. Eisenberg Award for Practical Application of Medical Decision-Making Research.