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| Author | : Begg, Rezaul |
| Publisher | : IGI Global |
| Total Pages | : 332 |
| Release | : 2006-01-31 |
| Genre | : Medical |
| ISBN | : 1591408504 |
"This book covers state-of-the-art applications in many areas of medicine and healthcare"--Provided by publisher.
| Author | : Adam Bohr |
| Publisher | : Academic Press |
| Total Pages | : 385 |
| Release | : 2020-06-21 |
| Genre | : Computers |
| ISBN | : 0128184396 |
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
| Author | : Rishabha Malviya |
| Publisher | : CRC Press |
| Total Pages | : 420 |
| Release | : 2023-03-10 |
| Genre | : Computers |
| ISBN | : 1000847020 |
Healthcare is one of the major success stories of our times. Medical science has improved rapidly, raising life expectancy around the world. However, as longevity increases, healthcare systems face growing demands for their services, rising costs, and a workforce that is struggling to meet the needs of its patients. Healthcare is one of the most critical sectors in the broader landscape of big data because of its fundamental role in a productive, thriving society. Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. The application of AI to healthcare data can literally be a matter of life and death. AI can assist doctors, nurses, and other healthcare workers in their daily work. AI in healthcare can enhance preventive care and quality of life, produce more accurate diagnoses and treatment plans, and lead to better patient outcomes overall. This book gives insights into the latest developments of applications of AI in biomedicine, including disease diagnostics, pharmaceutical processing, patient care and monitoring, biomedical information, and biomedical research. It also presents an outline of the recent breakthroughs in the application of AI in healthcare, describes a roadmap to building effective, reliable, and safe AI systems, and discusses the possible future direction of AI augmented healthcare systems. AI has countless applications in healthcare. Whether it’s being used to discover links between genetic codes, to power surgical robots or even to maximize hospital efficiency; AI has been a boon to the healthcare industry.
| Author | : K. Murugeswari |
| Publisher | : CRC Press |
| Total Pages | : 309 |
| Release | : 2024-05-15 |
| Genre | : Medical |
| ISBN | : 1040021379 |
Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data. Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient’s medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process. Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.
| Author | : Moein, Sara |
| Publisher | : IGI Global |
| Total Pages | : 326 |
| Release | : 2014-06-30 |
| Genre | : Medical |
| ISBN | : 146666147X |
Advanced conceptual modeling techniques serve as a powerful tool for those in the medical field by increasing the accuracy and efficiency of the diagnostic process. The application of artificial intelligence assists medical professionals to analyze and comprehend a broad range of medical data, thus eliminating the potential for human error. Medical Diagnosis Using Artificial Neural Networks introduces effective parameters for improving the performance and application of machine learning and pattern recognition techniques to facilitate medical processes. This book is an essential reference work for academicians, professionals, researchers, and students interested in the relationship between artificial intelligence and medical science through the use of informatics to improve the quality of medical care.
| Author | : Antonina Starita |
| Publisher | : World Scientific |
| Total Pages | : 368 |
| Release | : 1998-08-14 |
| Genre | : Computers |
| ISBN | : 9814544450 |
Interest in medical expert systems, neural networks and other artificial intelligence techniques is on the increase as more healthcare providers realise their potential, and engineers and scientists are discovering that medicine and healthcare are very fertile areas for developing new, or applying existing, intelligent algorithms to real problems. Intelligent systems make it possible to capture expert medical knowledge and to discover new knowledge so as to improve in-patient monitoring, data analysis and decision making, and hence the quality of healthcare.This book contains features which include: neural networks and expert systems techniques, as well as medical neural networks and expert systems. It should be of interest to managers, academics, engineers, scientists and medical practitioners involved in the funding, development and use of intelligent medical systems.
| Author | : Vishal Jain |
| Publisher | : CRC Press |
| Total Pages | : 311 |
| Release | : 2023-02-10 |
| Genre | : Technology & Engineering |
| ISBN | : 1000846520 |
Health care today is known to suffer from siloed and fragmented data, delayed clinical communications, and disparate workflow tools due to the lack of interoperability caused by vendor-locked health care systems, lack of trust among data holders, and security/privacy concerns regarding data sharing. The health information industry is ready for big leaps and bounds in terms of growth and advancement. This book is an attempt to unveil the hidden potential of the enormous amount of health information and technology. Throughout this book, we attempt to combine numerous compelling views, guidelines, and frameworks to enable personalized health care service options through the successful application of deep learning frameworks. The progress of the health-care sector will be incremental as it learns from associations between data over time through the application of suitable AI, deep net frameworks, and patterns. The major challenge health care is facing is the effective and accurate learning of unstructured clinical data through the application of precise algorithms. Incorrect input data leading to erroneous outputs with false positives is intolerable in healthcare as patients’ lives are at stake. This book is written with the intent to uncover the stakes and possibilities involved in realizing personalized health-care services through efficient and effective deep learning algorithms. The specific focus of this book will be on the application of deep learning in any area of health care, including clinical trials, telemedicine, health records management, etc.
| Author | : Yen-Wei Chen |
| Publisher | : Springer Nature |
| Total Pages | : 225 |
| Release | : 2019-11-18 |
| Genre | : Technology & Engineering |
| ISBN | : 3030326063 |
This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
| Author | : A. Carbonaro |
| Publisher | : IOS Press |
| Total Pages | : 178 |
| Release | : 2024-01-26 |
| Genre | : Computers |
| ISBN | : 1643684612 |
The data that must be processed in healthcare includes text, numbers, statistics, and images, and healthcare systems are continuously acquiring novel data from cutting-edge technologies like wearable devices. Semantic intelligence technologies, such as artificial intelligence, machine learning, and the internet of things, together with the hybrid methodologies which combine these approaches, are central to the development of the intelligent, knowledge-based systems now used in healthcare. This book, Roles and Challenges of Semantic Intelligence in Healthcare Cognitive Computing explores those emerging fields of science and technology in which cognitive computing techniques offer the effective solutions poised to impact healthcare in the foreseeable future, minimizing errors and improving the effectiveness of personalized care models. The book assesses the current landscape, and identifies the roles and challenges of integrating cognitive computing techniques into the widespread adoption of innovative smart healthcare solutions. Each chapter is the result of collaboration by experts from various domains, and provides a detailed overview of the potential offered by new technologies in the field. A wide spectrum of topics and emerging trends are covered, reflecting the multidisciplinary nature of healthcare and cognitive computing and including digital twins, eXplainable AI, AI-based decision-support systems in intensive care, and culinary healthcare, as well as the semantic internet of things (SIoT), natural language processing, and deep learning and graph models. The book presents new ideas which will facilitate collaboration among the different disciplines involved, and will be of interest to all those working in this rapidly evolving field.
| Author | : International Conference on Neural Networks and Expert Systems in Medicine and Healthcare |
| Publisher | : World Scientific Publishing Company Incorporated |
| Total Pages | : 350 |
| Release | : 1998 |
| Genre | : Artificial intelligence |
| ISBN | : 9789810236113 |
Interest in medical expert systems, neural networks and other artificial intelligence techniques is on the increase as more healthcare providers realize their potential, and engineers and scientists are discovering that medicine and healthcare are very fertile areas for developing new, or applying existing, intelligent algorithms to real problems. Intelligent systems make it possible to capture expert medical knowledge and to discover new knowledge so as to improve in-patient monitoring, data analysis and decision making, and hence the quality of healthcare. This book contains features which include: neural networks and expert systems techniques, as well as medical neural networks and expert systems. It should be of interest to managers, academics, engineers, scientists and medical practitioners involved in the funding, development and use of intelligent medical systems.
