Machine Learning In Dentistry

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Machine Learning in Dentistry

Ching-Chang Ko,Dinggang Shen,Li Wang
Machine Learning in Dentistry Book PDF

Author : Ching-Chang Ko,Dinggang Shen,Li Wang
Publisher : Springer Nature
Page : 186 pages
File Size : 40,9 Mb
Release : 2021-07-24
Category : Medical
ISBN : 9783030718817

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Machine Learning in Dentistry by Ching-Chang Ko,Dinggang Shen,Li Wang Pdf

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

Kaan Orhan,Rohan Jagtap
Artificial Intelligence in Dentistry Book PDF

Author : Kaan Orhan,Rohan Jagtap
Publisher : Springer Nature
Page : 363 pages
File Size : 53,5 Mb
Release : 2024-02-11
Category : Medical
ISBN : 9783031438271

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Artificial Intelligence in Dentistry by Kaan Orhan,Rohan Jagtap Pdf

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

Khalid Shaikh,Sreelekshmi Vivek Bekal,Hesham Fathi Ahmed Marei,Walid Shaaban Moustafa Elsayed,Dusan Surdilovic,Lubna Abdel Jawad
Artificial Intelligence in Dentistry Book PDF

Author : Khalid Shaikh,Sreelekshmi Vivek Bekal,Hesham Fathi Ahmed Marei,Walid Shaaban Moustafa Elsayed,Dusan Surdilovic,Lubna Abdel Jawad
Publisher : Springer Nature
Page : 205 pages
File Size : 52,9 Mb
Release : 2022-12-05
Category : Technology & Engineering
ISBN : 9783031197154

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Artificial Intelligence in Dentistry by Khalid Shaikh,Sreelekshmi Vivek Bekal,Hesham Fathi Ahmed Marei,Walid Shaaban Moustafa Elsayed,Dusan Surdilovic,Lubna Abdel Jawad Pdf

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

Dr Seema Jabeen,Dr Fozia Sultana,Dr Deepak Baby,Dr Robin Sabharwal
Role of Artificial Intelligence in Dentistry Current applications and future perspectives Book PDF

Author : Dr Seema Jabeen,Dr Fozia Sultana,Dr Deepak Baby,Dr Robin Sabharwal
Publisher : Perfect Writer Publishing
Page : 207 pages
File Size : 52,6 Mb
Release : 2024-05-14
Category : Antiques & Collectibles
ISBN : 9789360818777

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Role of Artificial Intelligence in Dentistry: Current applications and future perspectives by Dr Seema Jabeen,Dr Fozia Sultana,Dr Deepak Baby,Dr Robin Sabharwal Pdf

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.

AI for Dentists

Chris Friesz
AI for Dentists Book PDF

Author : Chris Friesz
Publisher : Independently Published
Page : 0 pages
File Size : 42,5 Mb
Release : 2023-08-14
Category : Electronic
ISBN : 9798857222577

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AI for Dentists by Chris Friesz Pdf

Artificial intelligence is rapidly transforming dentistry, but are you prepared to harness its possibilities? This comprehensive ebook equips dentists with an insider's guide to leveraging AI. Across 33 chapters, learn how AI is upgrading dental care delivery today - and where it's headed tomorrow. We demystify core technologies like machine learning and computer vision with simple explanations and real-world examples. See AI in action through case studies of algorithms enhancing diagnosis from radiographs, planning implants through CT scan analysis, designing customized treatment simulations, automating workflows, monitoring oral health via smart devices, and more. You'll get actionable recommendations for evaluating and integrating AI solutions, plus considerations like change management, transparent communication with patients, and ethical oversight critical for successful adoption. The future of dentistry with AI is bright. This indispensable guide illuminates the path forward - and prepares you to lead the way.

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller
Explainable AI Interpreting Explaining and Visualizing Deep Learning Book PDF

Author : Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller
Publisher : Springer Nature
Page : 435 pages
File Size : 55,7 Mb
Release : 2019-09-10
Category : Computers
ISBN : 9783030289546

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Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller Pdf

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.

Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare

Ilker Ozsahin
Applied Machine Learning and Multi Criteria Decision Making in Healthcare Book PDF

Author : Ilker Ozsahin
Publisher : Bentham Science Publishers
Page : 316 pages
File Size : 42,9 Mb
Release : 2021-11-18
Category : Computers
ISBN : 9781681088723

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Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare by Ilker Ozsahin Pdf

This book provides an ideal foundation for readers to understand the application of artificial intelligence (AI) and machine learning (ML) techniques to expert systems in the healthcare sector. It starts with an introduction to the topic and presents chapters which progressively explain decision-making theory that helps solve problems which have multiple criteria that can affect the outcome of a decision. Key aspects of the subject such as machine learning in healthcare, prediction techniques, mathematical models and classification of healthcare problems are included along with chapters which delve in to advanced topics on data science (deep-learning, artificial neural networks, etc.) and practical examples (influenza epidemiology and retinoblastoma treatment analysis). Key Features: - Introduces readers to the basics of AI and ML in expert systems for healthcare - Focuses on a problem solving approach to the topic - Provides information on relevant decision-making theory and data science used in the healthcare industry - Includes practical applications of AI and ML for advanced readers - Includes bibliographic references for further reading The reference is an accessible source of knowledge on multi-criteria decision-support systems in healthcare for medical consultants, healthcare policy makers, researchers in the field of medical biotechnology, oncology and pharmaceutical research and development.

Machine Learning Methods for Signal, Image and Speech Processing

M.A. Jabbar,MVV Prasad Kantipudi,Sheng-Lung Peng,Mamun Bin Ibne Reaz,Ana Maria Madureira
Machine Learning Methods for Signal Image and Speech Processing Book PDF

Author : M.A. Jabbar,MVV Prasad Kantipudi,Sheng-Lung Peng,Mamun Bin Ibne Reaz,Ana Maria Madureira
Publisher : CRC Press
Page : 257 pages
File Size : 45,8 Mb
Release : 2022-09-01
Category : Computers
ISBN : 9781000794748

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Machine Learning Methods for Signal, Image and Speech Processing by M.A. Jabbar,MVV Prasad Kantipudi,Sheng-Lung Peng,Mamun Bin Ibne Reaz,Ana Maria Madureira Pdf

The signal processing (SP) landscape has been enriched by recent advances in artificial intelligence (AI) and machine learning (ML), yielding new tools for signal estimation, classification, prediction, and manipulation. Layered signal representations, nonlinear function approximation and nonlinear signal prediction are now feasible at very large scale in both dimensionality and data size. These are leading to significant performance gains in a variety of long-standing problem domains like speech and Image analysis. As well as providing the ability to construct new classes of nonlinear functions (e.g., fusion, nonlinear filtering). This book will help academics, researchers, developers, graduate and undergraduate students to comprehend complex SP data across a wide range of topical application areas such as social multimedia data collected from social media networks, medical imaging data, data from Covid tests etc. This book focuses on AI utilization in the speech, image, communications and yirtual reality domains.

Artificial Intelligence in Dentistry

Swarnaa Chaturvedi
Artificial Intelligence in Dentistry Book PDF

Author : Swarnaa Chaturvedi
Publisher : Unknown
Page : 0 pages
File Size : 54,8 Mb
Release : 2022-10-03
Category : Medical
ISBN : 9798888330180

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Artificial Intelligence in Dentistry by Swarnaa Chaturvedi Pdf

Explains basic aspects of artificial intelligence in general Covers all up-to-date applications of artificial intelligence in dentistry in all branches in a consistent format Presents classical studies of applications in simple tabular form for better understanding Useful for dental undergraduates and postgraduates

Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing

Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing Book PDF

Author : Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Publisher : CRC Press
Page : 181 pages
File Size : 53,6 Mb
Release : 2020-12-23
Category : Technology & Engineering
ISBN : 9781000337136

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Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing by Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi Pdf

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

K. Gayathri Devi,Kishore Balasubramanian,Le Anh Ngoc
Machine Learning and Deep Learning Techniques for Medical Science Book PDF

Author : K. Gayathri Devi,Kishore Balasubramanian,Le Anh Ngoc
Publisher : CRC Press
Page : 413 pages
File Size : 41,7 Mb
Release : 2022-05-11
Category : Technology & Engineering
ISBN : 9781000582529

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Machine Learning and Deep Learning Techniques for Medical Science by K. Gayathri Devi,Kishore Balasubramanian,Le Anh Ngoc Pdf

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).

Machine Learning for Subsurface Characterization

Siddharth Misra,Hao Li,Jiabo He
Machine Learning for Subsurface Characterization Book PDF

Author : Siddharth Misra,Hao Li,Jiabo He
Publisher : Gulf Professional Publishing
Page : 442 pages
File Size : 41,7 Mb
Release : 2019-10-12
Category : Technology & Engineering
ISBN : 9780128177372

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Machine Learning for Subsurface Characterization by Siddharth Misra,Hao Li,Jiabo He Pdf

Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses on developing computational methods/algorithms that learn to recognize patterns and quantify functional relationships by processing large data sets, also referred to as the "big data." Deep learning (DL) is a subset of machine learning that processes "big data" to construct numerous layers of abstraction to accomplish the learning task. DL methods do not require the manual step of extracting/engineering features; however, it requires us to provide large amounts of data along with high-performance computing to obtain reliable results in a timely manner. This reference helps the engineers, geophysicists, and geoscientists get familiar with data science and analytics terminology relevant to subsurface characterization and demonstrates the use of data-driven methods for outlier detection, geomechanical/electromagnetic characterization, image analysis, fluid saturation estimation, and pore-scale characterization in the subsurface. Learn from 13 practical case studies using field, laboratory, and simulation data Become knowledgeable with data science and analytics terminology relevant to subsurface characterization Learn frameworks, concepts, and methods important for the engineer’s and geoscientist’s toolbox needed to support

Digital Dentistry

Maher Ali Rusho
Digital Dentistry Book PDF

Author : Maher Ali Rusho
Publisher : Book Saga Publications
Page : 590 pages
File Size : 51,6 Mb
Release : 2024-05-18
Category : Medical
ISBN : 9788197129148

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Digital Dentistry by Maher Ali Rusho Pdf

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.

Computational Techniques for Dental Image Analysis

Kamalanand, K.,Thayumanavan, B.,Jawahar, P. Mannar
Computational Techniques for Dental Image Analysis Book PDF

Author : Kamalanand, K.,Thayumanavan, B.,Jawahar, P. Mannar
Publisher : IGI Global
Page : 334 pages
File Size : 41,7 Mb
Release : 2018-10-30
Category : Medical
ISBN : 9781522562443

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Computational Techniques for Dental Image Analysis by Kamalanand, K.,Thayumanavan, B.,Jawahar, P. Mannar Pdf

With the technology innovations dentistry has witnessed in all its branches over the past three decades, the need for more precise diagnostic tools and advanced imaging methods has become mandatory across the industry. Recent advancements to imaging systems are playing an important role in efficient diagnoses, treatments, and surgeries. Computational Techniques for Dental Image Analysis provides innovative insights into computerized methods for automated analysis. The research presented within this publication explores pattern recognition, oral pathologies, and diagnostic processing. It is designed for dentists, professionals, medical educators, medical imaging technicians, researchers, oral surgeons, and students, and covers topics centered on easier assessment of complex cranio-facial tissues and the accurate diagnosis of various lesions at early stages.

Machine Learning in Medical Imaging

Xiaohuan Cao,Xuanang Xu,Islem Rekik,Zhiming Cui,Xi Ouyang
Machine Learning in Medical Imaging Book PDF

Author : Xiaohuan Cao,Xuanang Xu,Islem Rekik,Zhiming Cui,Xi Ouyang
Publisher : Springer Nature
Page : 501 pages
File Size : 47,7 Mb
Release : 2023-10-14
Category : Computers
ISBN : 9783031456763

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Machine Learning in Medical Imaging by Xiaohuan Cao,Xuanang Xu,Islem Rekik,Zhiming Cui,Xi Ouyang Pdf

The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.