Big data and artificial intelligence in ophthalmology - clinical application and future exploration
Author: Tae-im Kim
Publisher: Frontiers Media SA
Published: 2023-12-27
Total Pages: 101
ISBN-13: 2832541712
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Artificial Intelligence in Ophthalmology
Author: Andrzej Grzybowski
Publisher: Springer Nature
Published: 2021-10-13
Total Pages: 280
ISBN-13: 3030786013
DOWNLOAD EBOOKThis 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.
Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
Published: 2020-06-21
Total Pages: 385
ISBN-13: 0128184396
DOWNLOAD EBOOKArtificial 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
Artificial Intelligence and Ophthalmology
Author: Parul Ichhpujani
Publisher: Springer Nature
Published: 2021-04-22
Total Pages: 149
ISBN-13: 981160634X
DOWNLOAD EBOOKThe book helps to explore the vast expanse of artificial intelligence-based scientific content that has been published in the last few years. Ophthalmology has recently undergone a silent digital revolution, with machine learning and deep learning algorithms consistently outperforming human graders in studies published across the globe. It is high time that a resource that breaks this information behemoth into easily digestible bits comes to the fore. This book simplifies the complex mechanics of algorithms used in ophthalmology and vision science applications. It also tries to address potential ethical issues with machines entering our clinics and patients’ lives. Overall it is essential reading for ophthalmologists/eye care professionals interested in artificial intelligence and everyone who is looking for a deep dive into the exciting world of digital medicine.
Big data and artificial intelligence in ophthalmology
Author: Tae-im Kim
Publisher: Frontiers Media SA
Published: 2023-03-17
Total Pages: 143
ISBN-13: 2832517803
DOWNLOAD EBOOKArtificial Intelligence in Medical Imaging
Author: Erik R. Ranschaert
Publisher: Springer
Published: 2019-01-29
Total Pages: 373
ISBN-13: 3319948784
DOWNLOAD EBOOKThis book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Artificial Intelligence and Deep Learning in Pathology
Author: Stanley Cohen
Publisher: Elsevier Health Sciences
Published: 2020-06-02
Total Pages: 290
ISBN-13: 0323675379
DOWNLOAD EBOOKRecent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.
Current and Future Application of Artificial Intelligence in Clinical Medicine
Author: Jie Yang
Publisher: Bentham Science Publishers
Published: 2021-06-01
Total Pages: 154
ISBN-13: 1681088428
DOWNLOAD EBOOKCurrent 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.
Exploring “The Current Applications, Advantages & Disadvantages, Ethical Concerns & The Future Hold Of AI in Healthcare.”
Author: Dr. Hakim .K.Saboowala.
Publisher: Dr.Hakim Saboowala
Published: 2023-10-25
Total Pages: 79
ISBN-13:
DOWNLOAD EBOOKExploring “The Current Applications, Advantages & Disadvantages, Ethical Concerns & The Future Hold Of AI in Healthcare.” The healthcare industry is advancing ahead swiftly. For many healthcare organizations, being able to forecast which treatment techniques are likely to be successful with patients based on their makeup and treatment framework is a big step forward. Artificial intelligence has the potential to help healthcare providers in a variety of ways, including patient care and administrative tasks. The technology aims to mimic human cognitive functions, as it offers numerous advantages over traditional analytics and other clinical decision-making tools. Data becomes more precise and accurate, allowing the healthcare industry to have more insights into the processes and patient outcomes. Tus, an effort has been made in this E-Booklet to compile an overview of the use of artificial intelligence in radiology, cardiology, ophthalmology, and drug discovery process along with several relevant Illustrations for better understanding. …Dr. H. K. Saboowala. M.B.(Bom) .M.R.S.H.(London)
Precision Medicine and Artificial Intelligence
Author: Michael Mahler
Publisher: Academic Press
Published: 2021-03-12
Total Pages: 300
ISBN-13: 032385432X
DOWNLOAD EBOOKPrecision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions Provides background, milestone and examples of precision medicine Outlines the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using AI Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine
