Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: David Riaño,Szymon Wilk,Annette ten Teije
Publsiher: Springer
Total Pages: 429
Release: 2019-06-19
ISBN 10: 303021642X
ISBN 13: 9783030216429
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Lei Xing,Maryellen L. Giger,James K. Min
Publsiher: Academic Press
Total Pages: 568
Release: 2020-09-03
ISBN 10: 0128212586
ISBN 13: 9780128212585
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Deep Medicine

Deep Medicine
Author: Eric Topol
Publsiher: Basic Books
Total Pages: 400
Release: 2019-03-12
ISBN 10: 1541644646
ISBN 13: 9781541644649
Language: EN, FR, DE, ES & NL

Deep Medicine Book Review:

One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Niklas Lidströmer,Hutan Ashrafian
Publsiher: Springer
Total Pages: 1816
Release: 2022-03-17
ISBN 10: 9783030645724
ISBN 13: 303064572X
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

This book provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting. Artificial Intelligence in Medicine aims to give readers the required knowledge to apply artificial intelligence to clinical practice. The book is relevant to medical students, specialist doctors, and researchers whose work will be affected by artificial intelligence.

Artificial Intelligence In Medicine

Artificial Intelligence In Medicine
Author: Peter Szolovits
Publsiher: Routledge
Total Pages: 226
Release: 2019-03-13
ISBN 10: 0429728468
ISBN 13: 9780429728464
Language: EN, FR, DE, ES & NL

Artificial Intelligence In Medicine Book Review:

This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care. An introductory chapter describes the historical and technical foundations of the work and provides an overview of the current state of the art and research directions. The authors then describe four prototype computer programs that tackle difficult clinical problems in a manner similar to that of an expert physician. The programs presented are internist, a diagnostic aid that combines a large database of disease/manifestation associations with techniques for problem formulation; expert and the Glaucoma Program which use physiological models for the diagnosis and treatment of eye disease; mycin, a rule-based program for diagnosis and therapy selection for infectious diseases; and the Digitalis Therapy Advisor, which aids the physician in prescribing the right dose of the drug digitalis and also explains its actions.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Lia Morra,Silvia Delsanto,Loredana Correale
Publsiher: CRC Press
Total Pages: 152
Release: 2019-11-25
ISBN 10: 1000753085
ISBN 13: 9781000753080
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging Book Review:

This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Medical Applications of Artificial Intelligence

Medical Applications of Artificial Intelligence
Author: Arvin Agah
Publsiher: CRC Press
Total Pages: 526
Release: 2013-11-06
ISBN 10: 143988434X
ISBN 13: 9781439884348
Language: EN, FR, DE, ES & NL

Medical Applications of Artificial Intelligence Book Review:

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Applications of Artificial Intelligence reviews the research, focusing on state-of-the-art projects in the field. The book captures the breadth and depth of the medical applications of artificial intelligence, exploring new developments and persistent challenges.

Intelligence Based Medicine

Intelligence Based Medicine
Author: Anthony C. Chang
Publsiher: Academic Press
Total Pages: 550
Release: 2020-07-08
ISBN 10: 012816462X
ISBN 13: 9780128164624
Language: EN, FR, DE, ES & NL

Intelligence Based Medicine Book Review:

Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr,Kaveh Memarzadeh
Publsiher: Academic Press
Total Pages: 378
Release: 2020-06-21
ISBN 10: 0128184396
ISBN 13: 9780128184394
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Healthcare Book Review:

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

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Allan Tucker,Pedro Henriques Abreu,Jaime Cardoso,Pedro Pereira Rodrigues,David Riaño
Publsiher: Springer Nature
Total Pages: 505
Release: 2021-06-08
ISBN 10: 303077211X
ISBN 13: 9783030772116
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

This book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, held as a virtual event, in June 2021. The 28 full papers presented together with 30 short papers were selected from 138 submissions. The papers are grouped in topical sections on image analysis; predictive modelling; temporal data analysis; unsupervised learning; planning and decision support; deep learning; natural language processing; and knowledge representation and rule mining.

Machine Learning in Medicine

Machine Learning in Medicine
Author: Ayman El-Baz,Jasjit S. Suri
Publsiher: CRC Press
Total Pages: 312
Release: 2021-08-04
ISBN 10: 1351588745
ISBN 13: 9781351588744
Language: EN, FR, DE, ES & NL

Machine Learning in Medicine Book Review:

Machine Learning in Medicine covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several computer-aided diagnosis (CAD) systems, which have played an important role in the diagnosis of several diseases in the past decade, e.g., cancer detection, resulting in the development of several successful systems. New developments in machine learning may make it possible in the near future to develop machines that are capable of completely performing tasks that currently cannot be completed without human aid, especially in the medical field. This book covers such machines, including convolutional neural networks (CNNs) with different activation functions for small- to medium-size biomedical datasets, detection of abnormal activities stemming from cognitive decline, thermal dose modelling for thermal ablative cancer treatments, dermatological machine learning clinical decision support systems, artificial intelligence-powered ultrasound for diagnosis, practical challenges with possible solutions for machine learning in medical imaging, epilepsy diagnosis from structural MRI, Alzheimer's disease diagnosis, classification of left ventricular hypertrophy, and intelligent medical language understanding. This book will help to advance scientific research within the broad field of machine learning in the medical field. It focuses on major trends and challenges in this area and presents work aimed at identifying new techniques and their use in biomedical analysis, including extensive references at the end of each chapter.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publsiher: Springer
Total Pages: 373
Release: 2019-01-29
ISBN 10: 3319948784
ISBN 13: 9783319948782
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging Book Review:

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.

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
Author: Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
Publsiher: Academic Press
Total Pages: 290
Release: 2021-04-26
ISBN 10: 012823217X
ISBN 13: 9780128232170
Language: EN, FR, DE, ES & NL

Machine Learning and the Internet of Medical Things in Healthcare Book Review:

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Artificial Intelligence for Drug Development Precision Medicine and Healthcare

Artificial Intelligence for Drug Development  Precision Medicine  and Healthcare
Author: Mark Chang
Publsiher: CRC Press
Total Pages: 352
Release: 2020-05-12
ISBN 10: 1000767302
ISBN 13: 9781000767308
Language: EN, FR, DE, ES & NL

Artificial Intelligence for Drug Development Precision Medicine and Healthcare Book Review:

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Lalit Garg,Sebastian Basterrech,Chitresh Banerjee,Tarun K. Sharma
Publsiher: Springer Nature
Total Pages: 150
Release: 2021-10-29
ISBN 10: 9811662657
ISBN 13: 9789811662652
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Healthcare Book Review:

This book highlights the analytics and optimization issues in healthcare systems, proposes new approaches, and presents applications of innovative approaches in real facilities. In the past few decades, there has been an exponential rise in the application of swarm intelligence techniques for solving complex and intricate problems arising in healthcare. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. The primary objective of this book is to bring forward thorough, in-depth, and well-focused developments of hybrid variants of swarm intelligence algorithms and their applications in healthcare systems.

Precision Medicine and Artificial Intelligence

Precision Medicine and Artificial Intelligence
Author: Michael Mahler
Publsiher: Elsevier
Total Pages: 300
Release: 2021-04-15
ISBN 10: 0128202394
ISBN 13: 9780128202395
Language: EN, FR, DE, ES & NL

Precision Medicine and Artificial Intelligence Book Review:

Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on AI, its link to PM, and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as artificial intelligence (AI) has gained significant attention in the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems has enabled the generation of large amounts of data, making autoimmunity an ideal target for AI in the field of Precision Medicine (PM). 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 data sets 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 get a good overview of the field of Precision Medicine for autoimmune diseases and Artificial Intelligence Provides background, milestone and examples of precision medicine for autoimmune disease and artificial intelligence Proves the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using artificial intelligence

Artificial Intelligence for Data Driven Medical Diagnosis

Artificial Intelligence for Data Driven Medical Diagnosis
Author: Deepak Gupta,Utku Kose,Bao Le Nguyen,Siddhartha Bhattacharyya
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 326
Release: 2021-02-08
ISBN 10: 3110668327
ISBN 13: 9783110668322
Language: EN, FR, DE, ES & NL

Artificial Intelligence for Data Driven Medical Diagnosis Book Review:

This book collects research works of data-driven medical diagnosis done via Artificial Intelligence based solutions, such as Machine Learning, Deep Learning and Intelligent Optimization. Physical devices powered with Artificial Intelligence are gaining importance in diagnosis and healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.

Artificial Intelligence

Artificial Intelligence
Author: Sandeep Reddy
Publsiher: CRC Press
Total Pages: 336
Release: 2020-12-03
ISBN 10: 1000216861
ISBN 13: 9781000216868
Language: EN, FR, DE, ES & NL

Artificial Intelligence Book Review:

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.

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
Author: Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
Publsiher: Academic Press
Total Pages: 454
Release: 2020-11-20
ISBN 10: 0128202742
ISBN 13: 9780128202746
Language: EN, FR, DE, ES & NL

Machine Learning in Cardiovascular Medicine Book Review:

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Medical Imaging

Medical Imaging
Author: K.C. Santosh,Sameer Antani,DS Guru,Nilanjan Dey
Publsiher: CRC Press
Total Pages: 238
Release: 2019-08-20
ISBN 10: 0429642490
ISBN 13: 9780429642494
Language: EN, FR, DE, ES & NL

Medical Imaging Book Review:

The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.