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

Deep Learning Applications in Medical Imaging

Deep Learning Applications in Medical Imaging
Author: Sanjay Saxena,Sudip Paul
Publsiher: Unknown
Total Pages: 304
Release: 2020-08
ISBN 10: 9781799850717
ISBN 13: 1799850714
Language: EN, FR, DE, ES & NL

Deep Learning Applications in Medical Imaging Book Review:

Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

Applications of Machine Learning

Applications of Machine Learning
Author: Prashant Johri,Jitendra Kumar Verma,Sudip Paul
Publsiher: Springer Nature
Total Pages: 394
Release: 2020-05-04
ISBN 10: 9811533571
ISBN 13: 9789811533570
Language: EN, FR, DE, ES & NL

Applications of Machine Learning Book Review:

This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

Deep Learning for Biomedical Applications

Deep Learning for Biomedical Applications
Author: Utku Kose,Omer Deperlioglu,D. Jude Hemanth
Publsiher: CRC Press
Total Pages: 364
Release: 2021-07-20
ISBN 10: 1000406423
ISBN 13: 9781000406429
Language: EN, FR, DE, ES & NL

Deep Learning for Biomedical Applications Book Review:

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning
Author: Rani, Geeta,Tiwari, Pradeep Kumar
Publsiher: IGI Global
Total Pages: 586
Release: 2020-10-16
ISBN 10: 1799827437
ISBN 13: 9781799827436
Language: EN, FR, DE, ES & NL

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning Book Review:

By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

CT of the Heart

CT of the Heart
Author: U. Joseph Schoepf
Publsiher: Humana Press
Total Pages: 931
Release: 2019-04-01
ISBN 10: 1603272372
ISBN 13: 9781603272377
Language: EN, FR, DE, ES & NL

CT of the Heart Book Review:

This book is a comprehensive and richly-illustrated guide to cardiac CT, its current state, applications, and future directions. While the first edition of this text focused on what was then a novel instrument looking for application, this edition comes at a time where a wealth of guideline-driven, robust, and beneficial clinical applications have evolved that are enabled by an enormous and ever growing field of technology. Accordingly, the focus of the text has shifted from a technology-centric to a more patient-centric appraisal. While the specifications and capabilities of the CT system itself remain front and center as the basis for diagnostic success, much of the benefit derived from cardiac CT today comes from avant-garde technologies enabling enhanced visualization, quantitative imaging, and functional assessment, along with exciting deep learning, and artificial intelligence applications. Cardiac CT is no longer a mere tool for non-invasive coronary artery stenosis detection in the chest pain diagnostic algorithms; cardiac CT has proven its value for uses as diverse as personalized cardiovascular risk stratification, prediction, and management, diagnosing lesion-specific ischemia, guiding minimally invasive structural heart disease therapy, and planning cardiovascular surgery, among many others. This second edition is an authoritative guide and reference for both novices and experts in the medical imaging sciences who have an interest in cardiac CT.

Precision Medicine in Cardiovascular Disease Prevention

Precision Medicine in Cardiovascular Disease Prevention
Author: Seth S. Martin
Publsiher: Springer Nature
Total Pages: 194
Release: 2021
ISBN 10: 3030750558
ISBN 13: 9783030750558
Language: EN, FR, DE, ES & NL

Precision Medicine in Cardiovascular Disease Prevention Book Review:

"This book contains the current knowledge and potential future developments of precision medicine techniques including artificial intelligence, big data, mobile health, digital health and genetic medicine in the prevention of cardiovascular disease. It reviews the presently used advanced precision medicine techniques and fundamental principles that continue to act as guiding forces for many medical professionals in applying precision and preventative medical techniques in their day-to-day practices. Precision Medicine in Cardiovascular Disease Prevention describes current knowledge and potential future developments in this rapidly expanding field. It therefore provides a valuable resource for all practicing and trainee cardiologists looking to develop their knowledge and integrate precision medicine techniques into their practices"--Publisher's description.

Image Processing for Automated Diagnosis of Cardiac Diseases

Image Processing for Automated Diagnosis of Cardiac Diseases
Author: Kalpana Chauhan,Rajeev Kumar Chauhan
Publsiher: Academic Press
Total Pages: 240
Release: 2021-07-13
ISBN 10: 0323850650
ISBN 13: 9780323850650
Language: EN, FR, DE, ES & NL

Image Processing for Automated Diagnosis of Cardiac Diseases Book Review:

Image Processing for Automated Diagnosis of Cardiac Diseases highlights current and emerging technologies for the automated diagnosis of cardiac diseases. It presents concepts and practical algorithms, including techniques for the automated diagnosis of organs in motion using image processing. This book is suitable for biomedical engineering researchers, engineers and scientists in research and development, and clinicians who want to learn more about and develop advanced concepts in image processing to overcome the challenges of automated diagnosis of heart disease. Includes advanced techniques to improve diagnostic methods for various cardiac diseases Uses methods to improve the existing diagnostic features of echocardiographic machines Develops new diagnostic features for echocardiographic machines

Current and Future Role of Artificial Intelligence in Cardiac Imaging

Current and Future Role of Artificial Intelligence in Cardiac Imaging
Author: Steffen Erhard Petersen,Karim Lekadir,Alistair A. Young,Tim Leiner
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2020-10-09
ISBN 10: 2889660583
ISBN 13: 9782889660582
Language: EN, FR, DE, ES & NL

Current and Future Role of Artificial Intelligence in Cardiac Imaging Book Review:

Handbook of Robotic and Image Guided Surgery

Handbook of Robotic and Image Guided Surgery
Author: Mohammad Abedin-Nasab
Publsiher: Elsevier
Total Pages: 752
Release: 2019-09-25
ISBN 10: 0128142464
ISBN 13: 9780128142462
Language: EN, FR, DE, ES & NL

Handbook of Robotic and Image Guided Surgery Book Review:

Handbook of Robotic and Image-Guided Surgery provides state-of-the-art systems and methods for robotic and computer-assisted surgeries. In this masterpiece, contributions of 169 researchers from 19 countries have been gathered to provide 38 chapters. This handbook is 744 pages, includes 659 figures and 61 videos. It also provides basic medical knowledge for engineers and basic engineering principles for surgeons. A key strength of this text is the fusion of engineering, radiology, and surgical principles into one book. A thorough and in-depth handbook on surgical robotics and image-guided surgery which includes both fundamentals and advances in the field A comprehensive reference on robot-assisted laparoscopic, orthopedic, and head-and-neck surgeries Chapters are contributed by worldwide experts from both engineering and surgical backgrounds

Deep Learning in Healthcare

Deep Learning in Healthcare
Author: Yen-Wei Chen,Lakhmi C. Jain
Publsiher: Springer Nature
Total Pages: 218
Release: 2019-11-18
ISBN 10: 3030326063
ISBN 13: 9783030326067
Language: EN, FR, DE, ES & NL

Deep Learning in Healthcare Book Review:

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.

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

Handbook of Research on Applied Intelligence for Health and Clinical Informatics

Handbook of Research on Applied Intelligence for Health and Clinical Informatics
Author: Thakare, Anuradha Dheeraj,Wagh, Sanjeev J.,Bhende, Manisha Sunil,Anter, Ahmed M.,Gao, Xiao-Zhi
Publsiher: IGI Global
Total Pages: 470
Release: 2021-10-22
ISBN 10: 1799877108
ISBN 13: 9781799877103
Language: EN, FR, DE, ES & NL

Handbook of Research on Applied Intelligence for Health and Clinical Informatics Book Review:

Currently, informatics within the field of public health is a developing and growing industry. Clinical informatics are used in direct patient care by supplying medical practitioners with information that can be used to develop a care plan. Intelligent applications in clinical informatics facilitates with the technology-based solutions to analyze data or medical images and help clinicians to retrieve that information. Decision models aid with making complex decisions especially in uncertain situations. The Handbook of Research on Applied Intelligence for Health and Clinical Informatics is a comprehensive reference book that focuses on the study of resources and methods for the management of healthcare infrastructure and information. This book provides insights on how applied intelligence with deep learning, experiential learning, and more will impact healthcare and clinical information processing. The content explores the representation, processing, and communication of clinical information in natural and engineered systems. This book covers a range of topics including applied intelligence, medical imaging, telehealth, and decision support systems, and also looks at technologies and tools used in the detection and diagnosis of medical conditions such as cancers, diabetes, heart disease, lung disease, and prenatal syndromes. It is an essential reference source for diagnosticians, medical professionals, imaging specialists, data specialists, IT consultants, medical technologists, academicians, researchers, industrial experts, scientists, and students.

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 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.

Interpretable Machine Learning

Interpretable Machine Learning
Author: Christoph Molnar
Publsiher: Lulu.com
Total Pages: 314
Release: 2019
ISBN 10: 0244768528
ISBN 13: 9780244768522
Language: EN, FR, DE, ES & NL

Interpretable Machine Learning Book Review:

Pediatric Cardiology Board Review

Pediatric Cardiology Board Review
Author: Benjamin W. Eidem,Bryan C. Cannon,Jonathan N. Johnson,Anthony C. Chang,Frank Cetta
Publsiher: Lippincott Williams & Wilkins
Total Pages: 326
Release: 2016-06-20
ISBN 10: 149635124X
ISBN 13: 9781496351241
Language: EN, FR, DE, ES & NL

Pediatric Cardiology Board Review Book Review:

More than 900 board-style questions prepare you for certification and recertification! Based on the popular Mayo Clinic Pediatric Cardiology Review course, this highly regarded testing resource provides easy access to more than 900 questions and answers on every aspect of pediatric cardiology. Full explanations are provided for every question, helping you focus your areas for review and make the most of your study time.

Computational Intelligence for Machine Learning and Healthcare Informatics

Computational Intelligence for Machine Learning and Healthcare Informatics
Author: Rajshree Srivastava,Pradeep Kumar Mallick,Siddharth Swarup Rautaray,Manjusha Pandey
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 346
Release: 2020-06-22
ISBN 10: 3110648199
ISBN 13: 9783110648195
Language: EN, FR, DE, ES & NL

Computational Intelligence for Machine Learning and Healthcare Informatics Book Review:

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Explainable AI in Healthcare and Medicine

Explainable AI in Healthcare and Medicine
Author: Arash Shaban-Nejad,Martin Michalowski,David L. Buckeridge
Publsiher: Springer Nature
Total Pages: 344
Release: 2020-11-02
ISBN 10: 3030533522
ISBN 13: 9783030533526
Language: EN, FR, DE, ES & NL

Explainable AI in Healthcare and Medicine Book Review:

This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.

Machine Learning and Systems Biology in Genomics and Health

Machine Learning and Systems Biology in Genomics and Health
Author: Shailza Singh
Publsiher: Springer Nature
Total Pages: 135
Release: 2022
ISBN 10: 9811659931
ISBN 13: 9789811659935
Language: EN, FR, DE, ES & NL

Machine Learning and Systems Biology in Genomics and Health Book Review:

This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.