Intelligence Based Cardiology And Cardiac Surgery

Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine provides a comprehensive survey of artificial intelligence concepts and methodologies with real-life applications in cardiovascular medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and data science domains. The book's content consists of basic concepts of artificial intelligence and human cognition applications in cardiology and cardiac surgery. This portfolio ranges from big data, machine and deep learning, cognitive computing and natural language processing in cardiac disease states such as heart failure, hypertension and pediatric heart care. The book narrows the knowledge and expertise chasm between the data scientists, cardiologists and cardiac surgeons, inspiring clinicians to embrace artificial intelligence methodologies, educate data scientists about the medical ecosystem, and create a transformational paradigm for healthcare and medicine. Covers a wide range of relevant topics from real-world data, large language models, and supervised machine learning to deep reinforcement and federated learning Presents artificial intelligence concepts and their applications in many areas in an easy-to-understand format accessible to clinicians and data scientists Discusses using artificial intelligence and related technologies with cardiology and cardiac surgery in a myriad of venues and situations Delineates the necessary elements for successfully implementing artificial intelligence in cardiovascular medicine for improved patient outcomes Presents the regulatory, ethical, legal, and financial issues embedded in artificial intelligence applications in cardiology

Minimally invasive cardiac surgery(MICS) is an integral component of every future cardiac surgeon’s training. There continues to be a growing global demand towards less invasive surgical techniques. Both cardiologist and cardiac surgeon form "heart teams" to provide patients with novel, minimally invasive procedures, with all their benefits. Less invasive techniques are often complex and require special knowhow and skills. This book offers an innovative approach to learning, utilizing QR code technology, which refers the reader to essential audio-visual material, which, along with the didactic text, focuses on practical aspects of minimally invasive cardiac surgery. In modern Heart Teams, and with the advent of the hybrid era, surgeons will only be able to survive if they have state-of-the-art skills in less invasive technologies, which can be incorporated in the hybrid theatre and/or trans-catheter arena. This text accompanies the surgeon along this path, and provides clinical advice and practical solutions, beyond the necessary basic knowledge. Which courses to visit, which videos to watch, which centres to join for serious training? How best to exploit public and multimedia? How to consent a patient into a MICS procedure? How to set up a MICS program or practice? In the era of value driven outcomes, and a shift towards shorter and better patient journeys, MICS is a skill that no heart surgeon can be without. Minimally Invasive Cardiac Surgery: A Practical Guide is a teaching resource, reference book and manual written by surgeons who both operate and teach the procedures described within. Provides access to online resources via QR codes Includes links to videos and the e-version of the text Acts as a gateway to a huge choice of minimally invasive cardiac surgery materials

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

This second editionis a ground-breaking clinical text with a strong emphasis on rigorous evidence. Leaders in the field discuss best practice in the light of systematic reviews and randomised control trials, and how best to treat where the information is less clear. Case histories provide intriguing discussions on how to apply the evidence in real life situations. Evidence-based Cardiology also includes free access to the latest evidence, which is automatically posted on a companion website.

In the dynamic environment of healthcare, the fusion of Computational Intelligence and Healthcare Industry 4.0 has enabled remarkable advancements in disease detection and analysis. However, a critical challenge persists – the limitations of current computational intelligence approaches in dealing with small sample sizes. This setback hampers the performance of these innovative models, hindering their potential impact on medical applications. As we stand at the crossroads of technological innovation and healthcare evolution, the need for a solution becomes paramount. Advances in Computational Intelligence for the Healthcare Industry 4.0 is a comprehensive guide addressing the very heart of this challenge. Designed for academics, researchers, healthcare professionals, and stakeholders in Healthcare Industry 4.0, this book serves as a source of innovation. It not only illuminates the complexities of computational intelligence in healthcare but also provides a roadmap for overcoming the limitations posed by small sample sizes. From fundamental principles to innovative concepts, this book offers a holistic perspective, shaping the future of healthcare through the lens of computational intelligence and Healthcare Industry 4.0.

Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.

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

In the wake of the digital healthcare revolution, a critical challenge has emerged: the lack of a comprehensive understanding stemming from fragmented research. Despite the industry's meteoric rise, existing literature often compartmentalizes insights, neglecting the intricate multi-sector collaborations that fuel its progress. This gap hinders scholars and industry professionals, leaving them with a myopic view of the digital healthcare landscape. The urgent need for a holistic exploration has never been more apparent. Multi-Sector Analysis of the Digital Healthcare Industry is a groundbreaking book that will uncover the complexities of digital healthcare with a panoramic lens. This carefully curated collection of cross-functional chapters is a beacon guiding academics and industry specialists through the difficulties of the industry's past, present, and future. With experts from fields spanning medicine, technology, business, and regulatory sectors, this book addresses the limitations of current research but serves as a compass for those seeking a more profound comprehension of digital healthcare's collaborative dynamics.

In this book it is shown how this specialty has evolved over the past 20 years, with significant advances in diagnosis and palliative and definitive techniques for correction of cardiovascular diseases. The book contains 10 cahpters, which are showing the classical adult and pediatric cardiac surgery.

Part of the Monographs in Cardiac Surgery Series – Introducing ‘basic science into the cardiac operating room’. Fast systematic review of small areas of cardiac surgery including up-to-date information. This will allow more rapid publication than the alternative cardiac surgery ‘tomes’. This entry into the series will provide readers with a complete review of the current understanding in brain injury and the methods used to avoid or limit its effects on patient morbidity and mortality.