Artificial Intelligence: Cardiovascular Medicine / Surgery

Braunwald's Heart Disease, 12th ed. by Peter Libby; Robert O. Bonow; Douglas L. Mann, 2022 Current, comprehensive, and evidence-based Braunwald's Heart Disease remains the most trusted reference in the field and the leading source of reliable cardiology information for practitioners and trainees worldwide. The fully updated 12th Edition continues the tradition of excellence with dependable, state-of-the-art coverage of new drugs, new guidelines, more powerful imaging modalities, and recent developments in precision medicine that continue to change and advance the practice of cardiovascular medicine. Written and edited by global experts in the field, this award-winning text is an unparalleled multimedia reference for every aspect of this complex and fast-changing area. Offers balanced, dependable content on rapidly changing clinical science, clinical and translational research, and evidence-based medicine. Includes 76 new contributing authors and 14 new chapters that cover Artificial intelligence in Cardiovascular Medicine; Wearables; Influenza, Pandemics, COVID-19, and Cardiovascular Disease; Tobacco and Nicotine Products in Cardiovascular Disease; Cardiac Amyloidosis; Impact of the Environment on Cardiovascular Health, and more. Features a new introductory chapter Cardiovascular Disease: Past, Present, and Future by Eugene Braunwald, MD, offering his unique, visionary approach to the field of cardiology. Dr. Braunwald also curates the extensive, bimonthly online updates that include "Hot Off the Press" (with links to Practice Update) and "Late-Breaking Clinical Trials". Provides cutting-edge coverage of key topics such as proteomics and metabolomics, TAVR, diabetocardiology, and cardio-oncology. Contains 1,850 high-quality illustrations, radiographic images, algorithms, and charts, and provides access to 215 videos called out with icons in the print version. Highlights the latest AHA, ACC, and ESC guidelines to clearly summarize diagnostic criteria and clinical implications. Provides tightly edited, focused content for quick, dependable reference. Flexible format options include either one or two volumes in print, as well as a searchable eBook with ongoing updates. Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.

Intelligence-Based Cardiology and Cardiac Surgery by Anthony C. Chang; Robert Brisk; Francisco Lopez- Jimenez et al, 2024 Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine provides an especially timely multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies. It includes real-life applications in adult and pediatric cardiovascular medicine, spanning the life span from fetus to adult. Led by a senior cardiologist-data scientist and supported by renowned data scientists and cardiac clinicians with an ardent passion for artificial intelligence in cardiovascular medicine, the book provides a clinical interface between the medical and data science domains that is symmetric and realistic. The content consists of basic concepts and applications of artificial intelligence and human cognition in cardiology and cardiac surgery. This portfolio ranges from big data to machine and deep learning, as well as cognitive computing and natural language processing in cardiac disease states such as heart failure, hypertension, and pediatric cardiac care. Artificial intelligence tools are described from the intensive care unit setting to other venues, such as the outpatient clinic, catheterization laboratory, and operating room. Future applications in related areas, such as large language models, extended reality, and digital twins, are also discussed. The book encompasses more than 50 chapters written by cardiologists or cardiac surgeons. Each chapter provides sections on the current state of the art and future directions and concludes with major takeaways. A robust compendium of practical resources, such as a comprehensive glossary, best references, and other resources, is also included. The book narrows the knowledge and expertise chasm between data scientists, cardiologists, and cardiac surgeons, inspires these clinicians to embrace artificial intelligence methodologies, and educates data scientists about the cardiac ecosystem to create a transformational paradigm for cardiovascular healthcare that improves patient outcomes.

Machine Learning in Cardiovascular Medicine by Subhi J. Al'Aref; Gurpreet Singh; Lohendran Baskaran et al, 2021 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.

New Frontiers of Cardiovascular Screening Using Unobtrusive Sensors, AI, and IoT by Rohan Banerjee; Sanjay Kimbahune; Arpan Pal et al, 2022 New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI, and IoT provides insights into real-world problems in cardiovascular disease screening that can be addressed via AI, IoT and wearable based sensing. Non-Communicable Diseases (NCD) are surpassing CDS and emerging as the foremost cause of death. Hence, early screening of CVDs using wearable and other similar sensors is an extremely important global problem to solve. The digital health field is constantly changing, and this book provides a review of recent technology developments, offering unique coverage of processing time series physiological sensor data. The authors have developed this book with graduate and post graduate students in mind, making sure they provide an accessible entry point into the field. This book is particularly useful for engineers and computer scientists who want to build technologies that work in real world scenarios as it provides a practitioner's view/insights /tricks of the trade. Finally, this book helps researchers working on this important problem to quickly ramp up their knowledge and research to the state-of-the-art.

Nuclear Cardiology and Multimodal Cardiovascular Imaging: A Companion to Braunwald's Heart Disease by Marcelo Fernando Di Carli, 2022 Recent years have seen numerous advances in cardiovascular nuclear medicine technology, leading to more precise diagnoses and treatment and an expanded understanding of the molecular basis for cardiac disease. Nuclear Cardiology and Multimodal Cardiovascular Imaging is a one-stop, comprehensive guide to the diagnostic and clinical implications of this complex and increasingly important technology. Part of the Braunwald family of renowned cardiology references, it provides cutting-edge coverage of multimodal cardiac imaging along with case vignettes and integrated teaching content―ideal for cardiologists, cardiology fellows, radiologists, and nuclear medicine physicians.

Predicting Heart Failure by Issam Bait Bahadur; Kishor Kumar Sadasivuni; Hassen M. Ouakad et al, 2022 PREDICTING HEART FAILURE Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods focuses on the mechanics and symptoms of heart failure and various approaches, including conventional and modern techniques to diagnose it. This book also provides a comprehensive but concise guide to all modern cardiological practice, emphasizing practical clinical management in many different contexts. Predicting Heart Failure supplies readers with trustworthy insights into all aspects of heart failure, including essential background information on clinical practice guidelines, in-depth, peer-reviewed articles, and broad coverage of this fast-moving field. Readers will also find: Discussion of the main characteristics of cardiovascular biosensors, along with their open issues for development and application Summary of the difficulties of wireless sensor communication and power transfer, and the utility of artificial intelligence in cardiology Coverage of data mining classification techniques, applied machine learning and advanced methods for estimating HF severity and diagnosing and predicting heart failure Discussion of the risks and issues associated with the remote monitoring system Assessment of the potential applications and future of implantable and wearable devices in heart failure prediction and detection Artificial intelligence in mobile monitoring technologies to provide clinicians with improved treatment options, ultimately easing access to healthcare by all patient populations. Providing the latest research data for the diagnosis and treatment of heart failure, Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods is an excellent resource for nurses, nurse practitioners, physician assistants, medical students, and general practitioners to gain a better understanding of bedside cardiology.