DEMYSTIFYING RESEARCH FOR MEDICAL & HEALTHCARE STUDENTS All healthcare students need to understand research methods to be able to understand research articles and to actively engage in research where necessary. Most clinical programs include research training within their courses, and many students are required to undertake an assessed research project—both at undergraduate and postgraduate levels. Breaking down the jargon barriers of research methods, and designed for those new to the world of research, Demystifying Research is a straightforward and highly accessible guide to fundamental research methods, approaches, and skills. This student-friendly resource describes quantitative and qualitative research approaches, mixed research methods, research ethics and governance, research skills and more. Step-by-step, students learn to appraise research in scholarly articles, design a project, and conduct research in the lab, in clinical practice, and other real-life situations. Technical jargon and classic research are explained in plain English, while relevant theory is illustrated through relatable examples of research in practice. Designed to make learning about research easy, this valuable guide: Explains basic research methods in a direct and engaging style Breaks research methods down into manageable, easy-to-digest pieces Defines what research is, and provides an overview of its methods and methodologies Covers all key areas of research, including observational and experimental approaches, and clinical trials Includes real-life examples of successful student research projects Features a companion website containing lecture slides available to download in PowerPoint Demystifying Research is a must-have for undergraduate and postgraduate medical, nursing, other healthcare and social sciences students, as well as professionals looking to refresh their knowledge.

DEMYSTIFYING RESEARCH FOR MEDICAL & HEALTHCARE STUDENTS All healthcare students need to understand research methods to be able to understand research articles and to actively engage in research where necessary. Most clinical programs include research training within their courses, and many students are required to undertake an assessed research project—both at undergraduate and postgraduate levels. Breaking down the jargon barriers of research methods, and designed for those new to the world of research, Demystifying Research is a straightforward and highly accessible guide to fundamental research methods, approaches, and skills. This student-friendly resource describes quantitative and qualitative research approaches, mixed research methods, research ethics and governance, research skills and more. Step-by-step, students learn to appraise research in scholarly articles, design a project, and conduct research in the lab, in clinical practice, and other real-life situations. Technical jargon and classic research are explained in plain English, while relevant theory is illustrated through relatable examples of research in practice. Designed to make learning about research easy, this valuable guide: Explains basic research methods in a direct and engaging style Breaks research methods down into manageable, easy-to-digest pieces Defines what research is, and provides an overview of its methods and methodologies Covers all key areas of research, including observational and experimental approaches, and clinical trials Includes real-life examples of successful student research projects Features a companion website containing lecture slides available to download in PowerPoint Demystifying Research is a must-have for undergraduate and postgraduate medical, nursing, other healthcare and social sciences students, as well as professionals looking to refresh their knowledge.

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. - Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies - Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics - Unique case study approach provides readers with insights for practical clinical implementation

Are you new to research and daunted by the idea of constructing your own research proposal? Then this is the book you need! This book and accompanying web resource will answer all your questions about healthcare research by introducing you to the concepts, theories and practicalities surrounding it. The aim of both the book and the web resource is to help you to write a good healthcare research proposal – which is the starting point for any would-be student researcher. The book takes a look at the theory of research, the core of the topic, but also provides practical help and advice along the way. It takes the reader through the stages of the research process from developing the question to communicating the findings, demystifying the process on the way. The web resource works alongside the book, supplementing and expanding on the chapters, giving you the ability to prepare your very own research proposal. Explains key concepts in a clear, easy to understand way Includes activities and scenarios for you to work through which will also increase your understanding of research and research proposals Easily navigable web resource (www.researchproposalsforhealthprofessionals.com) Both book and website are arranged in the same order in which you would develop and write a research proposal Website includes downloadable research proposal template to complete step-by-step as you work through the book and web resource

The Principles and Practice of Narrative Medicine articulates the ideas, methods, and practices of narrative medicine. Written by the originators of the field, this book provides the authoritative starting place for any clinicians or scholars committed to learning of and eventually teaching or practicing narrative medicine.