Artificial Intelligence For Bone Disorder
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Artificial Intelligence For Bone Disorder
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Author : Rishabha Malviya
language : en
Publisher: John Wiley & Sons
Release Date : 2024-02-21
Artificial Intelligence For Bone Disorder written by Rishabha Malviya and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
ARTIFICIAL INTELLIGENCE FOR BONE DISORDER The authors have produced an invaluable resource that connects the fields of AI and bone treatment by providing essential insights into the current state and future of AI in bone condition diagnosis and therapy, as well as a methodical examination of machine learning algorithms, deep learning approaches, and their real-world uses. The book explores the use of artificial intelligence (AI) in the diagnosis and treatment of various bone illnesses. The integration of AI approaches in the fields of orthopedics, radiography, tissue engineering, and other areas related to bone are discussed in detail. It covers tissue engineering methods for bone regeneration and investigates the use of AI tools in this area, emphasizing the value of deep learning and how to use AI in tissue engineering efficiently. The book also covers diagnostic and prognostic uses of AI in orthopedics, such as the diagnosis of disorders involving the hip and knee as well as prognoses for therapies. Chapters also look at MRI, trabecular biomechanical strength, and other methods for diagnosing osteoporosis. Other issues the book examines include several uses of AI in pediatric orthopedics, 3D modeling, digital X-ray radiogrammetry, convolutional neural networks for customized care, and digital tomography. With information on the most recent developments and potential future applications, each chapter of the book advances our understanding of how AI might be used to diagnose and treat bone problems. Audience This book will serve as a guide for orthopedic experts, biomedical engineers, faculty members, research scholars, IT specialists, healthcare workers, and hospital administrators.
Artificial Intelligence For Neural Health
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Author : Rishabha Malviya
language : en
Publisher: CRC Press
Release Date : 2025-10-07
Artificial Intelligence For Neural Health written by Rishabha Malviya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-07 with Computers categories.
This book explores the transformative role of artificial intelligence (AI) in diagnosing and treating neurological disorders. It offers a comprehensive overview of how AI can enhance diagnostic accuracy, improve treatment plans, and ultimately lead to better patient outcomes in the realm of neural health. It covers a wide range of topics, including fundamental AI technologies and their relevance in neural health, detailed case studies demonstrating the application of AI in diagnosing and treating neurological conditions, and the ethical, legal, and social implications of using AI in healthcare. It also delves into future trends and innovations in AI-driven neural health solutions. The book is essential for healthcare professionals, AI researchers, and neuroscientists as it bridges the gap between cutting-edge AI technologies and practical medical applications.
Diagnosing Musculoskeletal Conditions Using Artificial Intelligence And Machine Learning To Aid Interpretation Of Clinical Imaging
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Author : Rakesh Kumar
language : en
Publisher: Elsevier
Release Date : 2024-11-16
Diagnosing Musculoskeletal Conditions Using Artificial Intelligence And Machine Learning To Aid Interpretation Of Clinical Imaging written by Rakesh Kumar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-16 with Science categories.
Bone deformations can lead to musculoskeletal disorders and negatively impact on individual quality of life. Early and accurate detection of bone deformation is crucial for effective medical intervention. Diagnosing Musculoskeletal Conditions Using Artificial Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging outlines a comprehensive approach that integrates Artificial Intelligence (AI) and Machine Learning (ML) techniques to identify bone deformations promptly and accurately. By leveraging advanced image analysis and pattern recognition, this approach aims to revolutionize the field of orthopedic diagnostics. This book covers challenges, technologies, applications, and future trends of AI and ML in Bone Deformation, addressing advanced and innovative techniques, frameworks, methodologies, and practical implementations of machine learning to get early predictions of Bone deformation. Written by experts in the field for researchers, surgeons, students, and instructors interested in musculoskeletal conditions. - Presents fundamental concepts and analysis of machine learning algorithms and diagnoses in bone deformation - Addresses human health issues related to bone deformation using a different machine learning algorithm - Provides innovative, new approaches for machine learning in musculoskeletal conditions with its future directions
Foundations Of Artificial Intelligence In Healthcare And Bioscience
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Author : Louis J. Catania
language : en
Publisher: Academic Press
Release Date : 2020-11-25
Foundations Of Artificial Intelligence In Healthcare And Bioscience written by Louis J. Catania and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Science categories.
Foundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians uses color-coded illustrations to explain AI from its basics to modern technologies. Other sections cover extensive, current literature research and citations regarding AI's role in the business and clinical aspects of health care. The book provides readers with a unique opportunity to appreciate AI technology in practical terms, understand its applications, and realize its profound influence on the clinical and business aspects of health care. Artificial Intelligence is a disruptive technology that is having a profound and growing influence on the business of health care as well as medical diagnosis, treatment, research and clinical delivery. The AI relationships in health care are complex, but understandable, especially when discussed and developed from their foundational elements through to their practical applications in health care. - Provides an illustrated, foundational guide and comprehensive descriptions of what Artificial Intelligence is and how it functions - Integrates a comprehensive discussion of AI applications in the business of health care - Presents in-depth clinical and AI-related discussions on diagnostic medicine, therapeutic medicine, and prevalent disease categories with an emphasis on immunology and genetics, the two categories most influenced by AI - Includes comprehensive coverage of a variety of AI treatment applications, including medical/pharmaceutical care, nursing care, stem cell therapies, robotics, and 10 common disease categories with AI applications
Explainable And Responsible Artificial Intelligence In Healthcare
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Author : Rishabha Malviya
language : en
Publisher: John Wiley & Sons
Release Date : 2025-03-04
Explainable And Responsible Artificial Intelligence In Healthcare written by Rishabha Malviya and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-04 with Computers categories.
This book presents the fundamentals of explainable artificial intelligence (XAI) and responsible artificial intelligence (RAI), discussing their potential to enhance diagnosis, treatment, and patient outcomes. This book explores the transformative potential of explainable artificial intelligence (XAI) and responsible AI (RAI) in healthcare. It provides a roadmap for navigating the complexities of healthcare-based AI while prioritizing patient safety and well-being. The content is structured to highlight topics on smart health systems, neuroscience, diagnostic imaging, and telehealth. The book emphasizes personalized treatment and improved patient outcomes in various medical fields. In addition, this book discusses osteoporosis risk, neurological treatment, and bone metastases. Each chapter provides a distinct viewpoint on how XAI and RAI approaches can help healthcare practitioners increase diagnosis accuracy, optimize treatment plans, and improve patient outcomes. Readers will find the book: explains recent XAI and RAI breakthroughs in the healthcare system; discusses essential architecture with computational advances ranging from medical imaging to disease diagnosis; covers the latest developments and applications of XAI and RAI-based disease management applications; demonstrates how XAI and RAI can be utilized in healthcare and what problems the technology faces in the future. Audience The main audience for this book is targeted to scientists, healthcare professionals, biomedical industries, hospital management, engineers, and IT professionals interested in using AI to improve human health.
Artificial Intelligence For Healthcare
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Author : Rishabha Malviya
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2025-04-21
Artificial Intelligence For Healthcare written by Rishabha Malviya and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-21 with Computers categories.
The book Artificial Intelligence for Healthcare: Machine Learning and Diagnostics explores how AI and machine learning are reshaping healthcare, focusing on diagnosis, patient care, and treatment across various specialties. It covers AI applications in fields such as cardiovascular care, orthopedics, emergency medicine, ENT, and remote patient monitoring. Additionally, the book discusses AI’s transformative role in brain tumor surgery, dentistry, and elder care, showcasing its power to personalize therapies, predict outcomes, and enhance outpatient efficiency. Key chapters examine AI in pathology, specifically in image analysis and digital pathology, and its expanding influence in maternal and fetal health. This essential guide provides healthcare practitioners, researchers, clinical experts, and students with insights into AI's practical uses and future potential, serving as a valuable reference for AI-driven diagnostic advancements and healthcare solutions.
Artificial Intelligence For Accurate Analysis And Detection Of Autism Spectrum Disorder
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Author : Kautish, Sandeep
language : en
Publisher: IGI Global
Release Date : 2021-06-25
Artificial Intelligence For Accurate Analysis And Detection Of Autism Spectrum Disorder written by Kautish, Sandeep and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Psychology categories.
Autism spectrum disorder (ASD) is known as a neuro-disorder in which a person may face problems in interaction and communication with people, amongst other challenges. As per medical experts, ASD can be diagnosed at any stage or age but is often noticeable within the first two years of life. If caught early enough, therapies and services can be provided at this early stage instead of waiting until it is too late. ASD occurrences appear to have increased over the last couple of years leading to the need for more research in the field. It is crucial to provide researchers and clinicians with the most up-to-date information on the clinical features, etiopathogenesis, and therapeutic strategies for patients as well as to shed light on the other psychiatric conditions often associated with ASD. In addition, it is equally important to understand how to detect ASD in individuals for accurate diagnosing and early detection. Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder discusses the early detection and diagnosis of autism spectrum disorder enabled by artificial intelligence technologies, applications, and therapies. This book will focus on the early diagnosis of ASD through artificial intelligence, such as deep learning and machine learning algorithms, for confirming diagnosis or suggesting the need for further evaluation of individuals. The chapters will also discuss the use of artificial intelligence technologies, such as medical robots, for enhancing the communication skills and the social and emotional skills of children who have been diagnosed with ASD. This book is ideally intended for IT specialists, data scientists, academicians, scholars, researchers, policymakers, medical practitioners, and students interested in how artificial intelligence is impacting the diagnosis and treatment of autism spectrum disorder.
Machine Learning And Deep Learning Applications In Pathogenic Microbiome Research
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Author : Gang Ye
language : en
Publisher: Frontiers Media SA
Release Date : 2024-09-30
Machine Learning And Deep Learning Applications In Pathogenic Microbiome Research written by Gang Ye and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-30 with Science categories.
The pathogenic microbiome is the community of microorganisms that live in humans or animals and cause disease. These microorganisms include bacteria, viruses, fungi, protozoa, etc. They usually live in the host's skin, mouth, intestinal tract, genitourinary tract, etc. Normally, there is a state of equilibrium between the host and these microorganisms, but when this equilibrium is disturbed, these microorganisms become the pathogenic microbiome and cause disease. To advance the field of microbiome research, artificial intelligence methods, especially machine learning and deep learning, have recently been used as important tools due to their powerful predictive and informative potential. Classical machine learning algorithms such as linear regression, random forests, support vector machines, etc. perform well on microbiome data. However, as algorithms have been iteratively updated, these models have long been relegated to the basics. Linear regression models are now more often used to interpret these models more intuitively by using the output of other models as input. Deep learning is a branch of machine learning that involves a large number of neural network structures. Deep learning relies on neurons whose role is to transform the input and propagate it forward to the next neuron. Deep learning is currently being used with spectacular success in areas such as image recognition, text processing and automatic translation. As a result, a growing number of researchers are attempting to apply deep learning techniques to biomedical data analysis. Although there are still challenges in practical applications, such as model interpretability, data availability, model evaluation and selection, machine learning and deep learning are very promising tools in pathogenic microbiome research. This Research Topic, therefore, aims to contribute to the latest advances in machine learning, especially deep learning, and to explore new applications of related techniques in pathogenic microbiome research, trying to find relationships between microbiome and human health as well as the environment by studying high-throughput sequencing data of microbes, laying the foundation for further applications for subsequent treatment or forensic identification. We welcome submissions of Original Research, Brief Research Report, Review, Mini-Review, Methods, Perspective and Opinion articles that focus on, but are not limited to, the utilization of machine learning and deep learning to address the following subtopics. 1. Classification and identification of pathogenic microorganisms 2. Virulence prediction of pathogenic microorganisms 3. Antimicrobial resistance prediction of pathogenic microorganisms 4. Population structure and epidemiology of pathogenic microorganisms-related diseases 5. Immunological studies of pathogenic microorganisms 6. Drug target prediction for pathogenic microorganisms-related diseases
Artificial Intelligence In Orthopaedic Surgery Made Easy
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Author : Filippo Familiari
language : en
Publisher: Springer Nature
Release Date : 2024-11-19
Artificial Intelligence In Orthopaedic Surgery Made Easy written by Filippo Familiari and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-19 with Medical categories.
This book is an essential reference guide for the use of artificial intelligence in orthopaedic surgery. It covers all related topics, from machine and deep learning, through practical applications in all orthopaedic sub-disciplines, to ethical issues and potential risks. International renowned experts equip the reader with solid scientific foundations and practical tips combining accurate literature reviews with high-quality original images. Addressing a hot topic for the present and next generation of medical specialists, this book is a must read for orthopaedic surgeons, radiologists and health informatic specialists alike.
Distributed Machine Learning And Computing
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Author : M. Hadi Amini
language : en
Publisher: Springer Nature
Release Date : 2024-05-28
Distributed Machine Learning And Computing written by M. Hadi Amini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-28 with Technology & Engineering categories.
This book focuses on a wide range of distributed machine learning and computing algorithms and their applications in healthcare and engineering systems. The contributors explore how these techniques can be applied to different real-world problems. It is suitable for students and researchers interested in conducting research in multidisciplinary areas that rely on distributed machine learning and computing techniques.