Build a solid foundation in surgical AI with this engaging, comprehensive guide for AI novicesMachine learning, neural networks, and computer vision in surgical education, practice, and research will soon be de rigueur. Written for surgeons without a background in math or computer science, Artificial Intelligence in Surgery provides everything you need to evaluate new technologies and make the right decisions about bringing AI into your practice.

This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehens...

The practice of modern medicine and biomedical research requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and carry out investigations. Biomedical Informatics provides both a conceptual framework and a practical inspiration for this swiftly emerging scientific discipline at the intersection of computer science, decision science, information science, cognitive science, and biom...

**WITH A FOREWORD BY SIDDHARTHA MUKHERJEEA renowned cardiologist and Harvard professor spells out the future digital shift of medicine — and how it will impact the lives not only of patients and health care professionals but of all humans.**Future care is virtual care: sensor-aided, digitally enabled, and powered by predictive analytics. Like most facets of modern life, human organs, too, are being digitally monitored. Sensors are well on their way to helping us proactively...

Over the years, medical informatics has matured into a true scientific discipline. Fundamental and applied aspects are now taught in various fields of health, including medicine, dentistry, pharmacy, nursing and public health. Medical informatics is also often included in the curricula of many other disciplines, including the life sciences, engineering and economics.Medical informatics is a complex and rapidly changing discipline. Relatively few books have been published on the sub...

Clinical Engineering is intended for professionals and students in the clinical engineering field who need to successfully deploy medical technologies. The book provides a broad reference to the core elements of the subject and draws from the expertise of a range of experienced authors. In addition to engineering skills, clinical engineers must be able to work with patients and with a range of professional staff, including technicians and clinicians, and with equipment manufacturers. They ...

In line with advances in digital and computing systems, artificial intelligence (AI) and machine learning (ML) technologies have transformed many aspects of medical and healthcare services, delivering tangible benefits to patents and the general public. This book is a sequel of the edition on “Artificial Intelligence and Machine Learning for Healthcare”. The first volume is focused on utilization of AI and ML for image and data analytics in the medical and healthcare domains. In this secon...

Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The...

This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience.

The complex challenges facing healthcare require innovative solutions that can make patient care more effective, easily available, and affordable. One such solution is the digital reconstruction of medicine that transitions much of patient care from hospitals, clinics, and offices to a variety of virtual settings. This reconstruction involves telemedicine, hospital-at-home services, mobile apps, remote sensing devices, clinical data analytics, and other cutting-edge technologies. T...

Dr. Wung is addressing an important component of critical care nursing: the role of technology in patient care. She has assembled top authors to provide current clinical information in the following areas: Sensory overload and technology in critical care; Alarm fatigue; Nurse-technology Interactions; Safety steps to prevent Infusion errors; Product design and medical devices for nurses ; Technologies to assess physiologic parameters (hemodynamics/cardio output); Technologies to support hem...

Clinical Informatics Literacy: 5000 Concepts That Every Informatician Should Know is about all aspects of clinical informatics, a subset of the larger field of biomedical informatics. Clinical Informatics is an applied field that exists at the intersection of the fields of medicine, computer science, information science, anthropology, human factors engineering, cognitive psychology and health services research. As such informaticians are required to have an extremely broad understanding of...