Big Data And Artificial Intelligence In Ophthalmology Clinical Application And Future Exploration
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Big Data And Artificial Intelligence In Ophthalmology Clinical Application And Future Exploration
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Author : Tae-im Kim
language : en
Publisher: Frontiers Media SA
Release Date : 2023-12-27
Big Data And Artificial Intelligence In Ophthalmology Clinical Application And Future Exploration written by Tae-im Kim 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 2023-12-27 with Medical categories.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Ai Adoption In Healthcare Industry 4 0
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Author : Mahima Jain
language : en
Publisher: Springer Nature
Release Date : 2025-05-22
Ai Adoption In Healthcare Industry 4 0 written by Mahima Jain and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-22 with Business & Economics categories.
This book focuses on the prominent innovative business models and employability implications of artificial intelligence in the healthcare industry 4.0. To do so, it draws upon a rich base of case studies from robotics, virtual assistants, precision medicine, etc., to highlight the possibilities and implications of AI on health care. The book is useful in a variety of ways to the different stakeholders of healthcare sector. It helps medical professionals to understand the impact of the present technologies being adopted and the potential of AI-based technology. The content is of use for the policy makers as it also highlights the managerial and research implications, challenges, opportunities posed by the adoption of AI in healthcare industry 4.0. The rich case study analysis in the area of adoption of AI in healthcare helps generate insights for the academicians and researchers of this field in terms of the parallels drawn between adoptions of AI in healthcare industry 4.0 across the world. It is also useful for management students to understand the key management perspective when healthcare organizations attempt to devise strategies/policies for adoption of AI-driven technologies and processes implementation.
Bioinformatics And Beyond
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Author : Moolchand Sharma
language : en
Publisher: CRC Press
Release Date : 2025-03-19
Bioinformatics And Beyond written by Moolchand Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-19 with Technology & Engineering categories.
This book is a comprehensive exploration of the dynamic interplay between bioinformatics and artificial intelligence (AI) within the healthcare landscape. This book introduces readers to the foundational principles of bioinformatics and AI, elucidating their integration and collaborative potential. Bioinformatics and Beyond: AI Applications in Healthcare explores the transformative impact of data-driven insights, showcasing the applications of machine learning in diagnostics, personalized medicine, and genomic advancements. The book unveils the pivotal role AI plays in accelerating pharmaceutical research. Moreover, it addresses the practical implementation of AI in clinical decision support systems, while also critically examining challenges and ethical considerations associated with these technologies. Finally, the book looks toward the future, envisioning emerging trends and technologies that promise to reshape the future of healthcare. Aimed at professionals, researchers, and students across diverse disciplines, this book serves as an invaluable guide to understanding and navigating the evolving landscape of AI applications in healthcare. This book is tailored to meet the needs of scientists, researchers, practitioners, professionals, and educators actively engaged in the realms of bioinformatics, artificial intelligence, and healthcare. It will be an indispensable resource for those seeking advanced strategies to address challenges and harness opportunities in the rapidly evolving fields of medical and biomedical research.
Current And Future Application Of Artificial Intelligence In Clinical Medicine
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Author : Jie Yang
language : en
Publisher: Bentham Science Publishers
Release Date : 2021-06-01
Current And Future Application Of Artificial Intelligence In Clinical Medicine written by Jie Yang and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-01 with Medical categories.
Current and Future Application of Artificial Intelligence in Clinical Medicine presents updates on the application of machine learning and deep learning techniques in medical procedures. . Chapters in the volume have been written by outstanding contributors from cancer and computer science institutes with the goal of providing updated knowledge to the reader. Topics covered in the book include 1) Artificial Intelligence (AI) applications in cancer diagnosis and therapy, 2) Updates in AI applications in the medical industry, 3) the use of AI in studying the COVID-19 pandemic in China, 4) AI applications in clinical oncology (including AI-based mining for pulmonary nodules and the use of AI in understanding specific carcinomas), 5) AI in medical imaging. Each chapter presents information on related sub topics in a reader friendly format. The combination of expert knowledge and multidisciplinary approaches highlighted in the book make it a valuable source of information for physicians and clinical researchers active in the field of cancer diagnosis and treatment (oncologists, oncologic surgeons, radiation oncologists, nuclear medicine physicians, and radiologists) and computer science scholars seeking to understand medical applications of artificial intelligence.
Artificial Intelligence In Ophthalmology
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Author : Andrzej Grzybowski
language : en
Publisher: Springer
Release Date : 2022-10-15
Artificial Intelligence In Ophthalmology written by Andrzej Grzybowski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-15 with Medical categories.
This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.
Integrating Artificial Intelligence Machine Learning And Big Data With Genetic Testing And Genomic Medicine To Enable Earlier Personalized Health Interventions
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Author : Sambasiva Rao Suura
language : en
Publisher: Deep Science Publishing
Release Date : 2025-04-13
Integrating Artificial Intelligence Machine Learning And Big Data With Genetic Testing And Genomic Medicine To Enable Earlier Personalized Health Interventions written by Sambasiva Rao Suura and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-13 with Computers categories.
The convergence of Artificial Intelligence (AI), Machine Learning (ML), and Big Data with genetic testing and genomic medicine marks a transformative era in healthcare. This book explores the powerful synergy among these domains and their potential to reshape the way we understand, predict, and treat disease—ushering in a new age of personalized medicine. Genomic medicine, with its promise of tailoring healthcare based on an individual's genetic profile, has made significant strides in recent years. However, the vast and complex nature of genomic data presents both opportunities and challenges. This is where AI and ML come into play—offering advanced algorithms and predictive models capable of processing enormous datasets, identifying patterns, and generating actionable insights that were previously beyond human capability. Big Data technologies further support this integration by enabling the collection, storage, and analysis of genomic, clinical, lifestyle, and environmental information at an unprecedented scale and speed. The aim of this book is to provide readers with a comprehensive understanding of how AI, ML, and Big Data are being leveraged to enhance the precision, timing, and impact of genetic testing and interventions. From identifying predispositions to chronic conditions and rare diseases, to optimizing treatment plans and monitoring patient outcomes in real-time, the potential applications are vast and growing. We explore current advancements, real-world applications, and future directions in this rapidly evolving field. Whether you are a researcher, clinician, data scientist, or policy maker, this book offers valuable insights into the opportunities and ethical considerations that lie at the intersection of technology and genomic science. By harnessing these powerful technologies, we are moving toward a future where healthcare is not only reactive but predictive and preventative—tailored to each individual at the molecular level. This is the promise of personalized medicine, and the journey begins here.
Generative Ai Techniques For Sustainability In Healthcare Security
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Author : Shah, Imdad Ali
language : en
Publisher: IGI Global
Release Date : 2024-12-02
Generative Ai Techniques For Sustainability In Healthcare Security written by Shah, Imdad Ali and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-02 with Medical categories.
In a world of constant change, sustainability and technology emerge as pivotal elements in healthcare. Generative artificial intelligence (AI) presents the capabilities of more accurate diagnoses, personalized treatment plans, and drug discovery, while certain operations in healthcare, such as managing relationships with healthcare systems often necessitate a human touch, these processes can be augmented by generative AI. Sustainability and health security are becoming increasingly important. The relationship between sustainability and health security is significant, as environmental factors such as air pollution, climate change, and access to green spaces can all affect human health. Generative AI Techniques for Sustainability in Healthcare Security provides a comprehensive understanding of generative AI techniques and their application for sustainability in health security, empowering readers with the knowledge needed to leverage these cutting-edge technologies effectively. Covering topics such as disease detection, drug discovery and development, and sustainability, this book is a valuable resource for scientists, medical professionals, hospital administrators, researchers, technologists, academicians, and more.
Microbiome And Machine Learning Volume Ii
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Author : Erik Bongcam-Rudloff
language : en
Publisher: Frontiers Media SA
Release Date : 2024-10-24
Microbiome And Machine Learning Volume Ii written by Erik Bongcam-Rudloff 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 2024-10-24 with Science categories.
Due to the success of Microbiome and Machine Learning, which collected research results and perspectives of researchers working in the field of machine learning (ML) applied to the analysis of microbiome data, we are launching the second volume to collate any new findings in the field to further our understanding and encourage the participation of experts worldwide in the discussion. The success of ML algorithms in the field is substantially due to their capacity to process high-dimensional data and deal with uncertainty and noise. However, to maximize the combinatory potential of these emerging fields (microbiome and ML), researchers have to deal with some aspects that are complex and inherently related to microbiome data. Microbiome data are convoluted, noisy and highly variable, and non-standard analytical methodologies are required to unlock their clinical and scientific potential. Therefore, although a wide range of statistical modelling and ML methods are available, their application is only sometimes optimal when dealing with microbiome data.
Efficient Artificial Intelligence Ai In Ophthalmic Imaging
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Author : Yanda Meng
language : en
Publisher: Frontiers Media SA
Release Date : 2025-01-07
Efficient Artificial Intelligence Ai In Ophthalmic Imaging written by Yanda Meng 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 2025-01-07 with Medical categories.
Ophthalmic imaging techniques, such as optical coherence tomography (OCT), OCT angiography (OCTA), fundus photography, and fluorescein angiography, generate vast amounts of visual data, allowing for a detailed examination of the eye's structure and function. These images provide invaluable insights into the presence and progression of various ocular diseases, such as age-related macular degeneration, diabetic retinopathy, and glaucoma. While ophthalmologists possess expertise in interpreting these images, the manual analysis of large datasets can be time-consuming, prone to errors, and subject to inter-observer variability. Artificial Intelligence (AI) based approaches have emerged as promising tools to augment the diagnostic capabilities of ophthalmologists, enabling faster and more accurate assessments. This proposal aims to explore and develop innovative approaches, including but not limited to transfer learning, activate learning, semi-supervised learning, weakly supervised learning, meta-learning, graph neural networks, multimodal learning, and federated learning, etc. to enhance the efficiency and effectiveness of AI in ophthalmic imaging. This collection aims to promote research that improves the accuracy, scalability, interpretability, and generalization of AI models for ophthalmic imaging. This Research Topic welcomes manuscripts on the following themes: ● Annotation-efficient AI: Manual data annotation is a labor-intensive and time consuming process that often poses challenges in terms of scalability, cost, and subjectivity. This topic aims to explore innovative approaches and techniques to develop annotation-efficient AI models that can leverage minimal data annotation while maintaining high performance and generalization, such as activate learning, semi-/weakly/un-/self-supervised learning, etc.