Analysis of Medical Modalities for Improved Diagnosis in Modern Healthcare

Analysis of Medical Modalities for Improved Diagnosis in Modern Healthcare
Author: Varun Bajaj
Publisher: CRC Press
Total Pages: 345
Release: 2021-08-10
Genre: Computers
ISBN: 1000400220

In modern healthcare, various medical modalities play an important role in improving the diagnostic performance in healthcare systems for various applications, such as prosthesis design, surgical implant design, diagnosis and prognosis, and detection of abnormalities in the treatment of various diseases. Analysis of Medical Modalities for Improved Diagnosis in Modern Healthcare discusses the uses of analysis, modeling, and manipulation of modalities, such as EEG, ECG, EMG, PCG, EOG, MRI, and FMRI, for an automatic identification, classification, and diagnosis of different types of disorders and physiological states. The analysis and applications for post-processing and diagnosis are much-needed topics for researchers and faculty members all across the world in the field of automated and efficient diagnosis using medical modalities. To meet this need, this book emphasizes real-time challenges in medical modalities for a variety of applications for analysis, classification, identification, and diagnostic processes of healthcare systems. Each chapter starts with the introduction, need and motivation of the medical modality, and a number of applications for the identification and improvement of healthcare systems. The chapters can be read independently or consecutively by research scholars, graduate students, faculty members, and practicing scientists who wish to explore various disciplines of healthcare systems, such as computer sciences, medical sciences, and biomedical engineering. This book aims to improve the direction of future research and strengthen research efforts of healthcare systems through analysis of behavior, concepts, principles, and case studies. This book also aims to overcome the gap between usage of medical modalities and healthcare systems. Several novel applications of medical modalities have been unlocked in recent years, therefore new applications, challenges, and solutions for healthcare systems are the focus of this book.

IOT with Smart Systems

IOT with Smart Systems
Author: Tomonobu Senjyu
Publisher: Springer Nature
Total Pages: 804
Release: 2022-01-05
Genre: Technology & Engineering
ISBN: 9811639450

This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Fifth International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2021), held in Ahmedabad, India. The book is divided into two volumes. It discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.

Machine Learning and Deep Learning Techniques for Medical Science

Machine Learning and Deep Learning Techniques for Medical Science
Author: K. Gayathri Devi
Publisher: CRC Press
Total Pages: 413
Release: 2022-05-11
Genre: Technology & Engineering
ISBN: 1000582523

The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).

Natural Language Processing In Healthcare

Natural Language Processing In Healthcare
Author: Satya Ranjan Dash
Publisher: CRC Press
Total Pages: 261
Release: 2022-09-13
Genre: Computers
ISBN: 1000624684

Natural Language Processing In Healthcare: A Special Focus on Low Resource Languages covers the theoretical and practical aspects as well as ethical and social implications of NLP in healthcare. It showcases the latest research and developments contributing to the rising awareness and importance of maintaining linguistic diversity. The book goes on to present current advances and scenarios based on solutions in healthcare and low resource languages and identifies the major challenges and opportunities that will impact NLP in clinical practice and health studies.

Fatigue: Physiology and Pathology

Fatigue: Physiology and Pathology
Author: Slawomir Kujawski
Publisher: Frontiers Media SA
Total Pages: 109
Release: 2024-02-15
Genre: Science
ISBN: 2832544711

In 1917, the president of the American Psychological Association at that time, Raymond Dodge, wrote “I have no expectation that the laws of mental fatigue will be formulated in the immediate future”. Remarkably, despite continuous efforts over a period of more than 100 years, a mature theory of the origins and neural mechanisms of mental fatigue has yet to be achieved. Physical fatigue is defined as “the transient inability of muscles to maintain optimal physical performance, and is made more severe by intense physical exercise”. Mental fatigue could be phrased as “a transient decrease in maximal cognitive performance resulting from prolonged periods of cognitive activity”. Currently, the mechanism underlying mental fatigue is still yet to be discovered. Chronic fatigue is one of the symptoms that may occur in numerous chronic disorders, such as hypertension, multiple sclerosis, fibromyalgia, and heart fail. Currently, there is no cure for ME/CFS. Chronic fatigue seems to be a relatively common, yet undertreated symptom. Presumably, increasing knowledge of physiological mechanisms underlying fatigue might potentially lead to an improvement in the efficacy of therapy for various disorders. Therefore, the goal of the current Research Topic is to collect papers on both physiology of fatigue as well as mechanism underlying pathologies, as ME/CFS. Also, papers on clinical trials involving subjects with chronic fatigue, or patients with ME/CFS are welcomed.

Improving Diagnosis in Health Care

Improving Diagnosis in Health Care
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
Total Pages: 473
Release: 2015-12-29
Genre: Medical
ISBN: 0309377722

Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

Evidence-Based Medicine and the Changing Nature of Health Care

Evidence-Based Medicine and the Changing Nature of Health Care
Author: Institute of Medicine
Publisher: National Academies Press
Total Pages: 202
Release: 2008-09-06
Genre: Medical
ISBN: 0309113695

Drawing on the work of the Roundtable on Evidence-Based Medicine, the 2007 IOM Annual Meeting assessed some of the rapidly occurring changes in health care related to new diagnostic and treatment tools, emerging genetic insights, the developments in information technology, and healthcare costs, and discussed the need for a stronger focus on evidence to ensure that the promise of scientific discovery and technological innovation is efficiently captured to provide the right care for the right patient at the right time. As new discoveries continue to expand the universe of medical interventions, treatments, and methods of care, the need for a more systematic approach to evidence development and application becomes increasingly critical. Without better information about the effectiveness of different treatment options, the resulting uncertainty can lead to the delivery of services that may be unnecessary, unproven, or even harmful. Improving the evidence-base for medicine holds great potential to increase the quality and efficiency of medical care. The Annual Meeting, held on October 8, 2007, brought together many of the nation's leading authorities on various aspects of the issues - both challenges and opportunities - to present their perspectives and engage in discussion with the IOM membership.

Deep Learning for Smart Healthcare

Deep Learning for Smart Healthcare
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.

Improving Healthcare Quality in Europe Characteristics, Effectiveness and Implementation of Different Strategies

Improving Healthcare Quality in Europe Characteristics, Effectiveness and Implementation of Different Strategies
Author: OECD
Publisher: OECD Publishing
Total Pages: 447
Release: 2019-10-17
Genre:
ISBN: 9264805907

This volume, developed by the Observatory together with OECD, provides an overall conceptual framework for understanding and applying strategies aimed at improving quality of care. Crucially, it summarizes available evidence on different quality strategies and provides recommendations for their implementation. This book is intended to help policy-makers to understand concepts of quality and to support them to evaluate single strategies and combinations of strategies.

Smart Medical Imaging for Diagnosis and Treatment Planning

Smart Medical Imaging for Diagnosis and Treatment Planning
Author: Nilanjan Dey
Publisher: CRC Press
Total Pages: 259
Release: 2024-07-31
Genre: Computers
ISBN: 1040105629

This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques. It shows how smart health technologies leverage artificial intelligence (AI) and big data analytics to provide more accurate and efficient diagnosis and treatment planning. In search for innovative and novel methods and techniques for health technologies and medical data processing, the book • Discusses applications of Artificial Intelligence, Data Science, Machine Learning, Deep Learning, the Internet of Things, Big Data, Cloud Computing; • Includes use of electronic patient records in healthcare, analysis of big data in medical diagnosis, reliability, and challenges of EPR and EHR in smart healthcare; • Explores evolving techniques for smart healthcare, its application in medical imaging and prediction in the fields of treatment planning; • Provides recent studies in AI-driven healthcare technologies and medical imaging to outline insight into smart healthcare technologies; • Discusses the role of big data in smart healthcare, computing techniques for healthcare for medical diagnosis and treatment planning; • Encompasses the ethical and legal challenges of using smart healthcare and medical data. This book serves as a valuable reference for researchers working on smart health technologies. Researchers of medical imaging, artificial intelligence, and data science along with healthcare domain will find it a great resource as well.