Computing and artificial intelligence in digital therapeutics
| Author | : Pengwei Hu |
| Publisher | : Frontiers Media SA |
| Total Pages | : 209 |
| Release | : 2024-01-15 |
| Genre | : Medical |
| ISBN | : 2832537731 |
Computing And Artificial Intelligence In Digital Therapeutics
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Artificial Intelligence in Healthcare
| 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
Psychodynamic Treatment Research
| Author | : Nancy E. Miller |
| Publisher | : |
| Total Pages | : 616 |
| Release | : 1993 |
| Genre | : Psychology |
| ISBN | : |
"As we enter a new era of scientific evaluation and acceptance of Freud's ideas, psychodynamic practitioners need to be aware of the most valid and clinically useful findings relevant to their everyday work with patients. This handbook meets that need by integrating the best contributions of the clinical psychoanalytic literature with the latest generation of clinical-quantitative research, and translating these findings into pragmatic clinical wisdom about what works and what doesn't." "In twenty-six chapters, forty-nine leading authorities and clinician-researchers discuss what is known about selecting patients, defining treatments, and measuring key processes and outcomes. The findings include which curative factors are effective; how the patient-therapist alliance can be a major predictor of treatment success; new transference, defense, insight, and internalization measures; prescriptions for improved case studies; pros and cons of the DSMs; and the role of psychotherapy manuals." "This comprehensive volume not only offers the clinician the latest in psychodynamic research and thinking but can guide those who wish to shape their clinical hypothesis into a study. By reviewing the central clinical concepts and techniques of psychodynamic psychotherapy and by providing the necessary empirical documentation to support their validity and clinical relevance, Psychodynamic Treatment Research makes an important contribution to mapping out the future of therapy."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved
AI-First Healthcare
| Author | : Kerrie L. Holley |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 222 |
| Release | : 2021-04-19 |
| Genre | : Business & Economics |
| ISBN | : 1492063126 |
AI is poised to transform every aspect of healthcare, including the way we manage personal health, from customer experience and clinical care to healthcare cost reductions. This practical book is one of the first to describe present and future use cases where AI can help solve pernicious healthcare problems. Kerrie Holley and Siupo Becker provide guidance to help informatics and healthcare leadership create AI strategy and implementation plans for healthcare. With this book, business stakeholders and practitioners will be able to build knowledge, a roadmap, and the confidence to support AIin their organizations—without getting into the weeds of algorithms or open source frameworks. Cowritten by an AI technologist and a medical doctor who leverages AI to solve healthcare’s most difficult challenges, this book covers: The myths and realities of AI, now and in the future Human-centered AI: what it is and how to make it possible Using various AI technologies to go beyond precision medicine How to deliver patient care using the IoT and ambient computing with AI How AI can help reduce waste in healthcare AI strategy and how to identify high-priority AI application
Artificial Intelligence in Behavioral and Mental Health Care
| Author | : David D. Luxton |
| Publisher | : Academic Press |
| Total Pages | : 309 |
| Release | : 2015-09-10 |
| Genre | : Psychology |
| ISBN | : 0128007923 |
Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
Future of Health Technology
| Author | : Renata Glowacka Bushko |
| Publisher | : IOS Press |
| Total Pages | : 306 |
| Release | : 2002 |
| Genre | : Medical |
| ISBN | : 9781586030919 |
This text provides a comprehensive vision of the future of health technology by looking at the ways to advance medical technologies, health information infrastructure and intellectual leadership. It also explores technology creations, adoption processes and the impact of evolving technologies.
Artificial Intelligence in Drug Discovery
| Author | : Nathan Brown |
| Publisher | : Royal Society of Chemistry |
| Total Pages | : 425 |
| Release | : 2020-11-04 |
| Genre | : Computers |
| ISBN | : 1839160543 |
Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.
Artificial Intelligence in Medical Imaging
| Author | : Erik R. Ranschaert |
| Publisher | : Springer |
| Total Pages | : 369 |
| Release | : 2019-01-29 |
| Genre | : Medical |
| ISBN | : 3319948784 |
This 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 |
| Total Pages | : 290 |
| Release | : 2020-06-02 |
| Genre | : Medical |
| ISBN | : 0323675379 |
Recent 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.
Artificial Intelligence
| Author | : Sandeep Reddy |
| Publisher | : CRC Press |
| Total Pages | : 287 |
| Release | : 2020-12-02 |
| Genre | : Business & Economics |
| ISBN | : 1000216861 |
The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery. Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.
