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.

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.

Drawing Closer to God One Decision at a Time On an average day, people makes countless decisions: Should I get out of bed or hit the snooze button? What should I have for breakfast? Where should we go for this year's vacation? While some decisions are easy to make, others can leave individuals paralyzed and full of anxiety. As Christians living in an increasingly individualistic society, what's the best strategy for making decisions that honor God while becoming more like him in the process? Writing from her own experience and pointing to biblical examples, Aimee Joseph offers a biblical and theological framework for decision-making. She explains God's design for humans as decision-makers, the biblical model for making choices, common wrong approaches, practical tips, and what to do when you've made a poor decision. With the philosophy that "as we shape our decisions, our decisions shape us," Joseph teaches readers how to worship and draw closer to Christ through their daily decisions. Practical: Equips Christians to make decisions as God's image bearers Applicable: Features study questions and helpful resources, including "The Dashboard of Decisions" and a decision-making flowchart Published in Partnership with the Gospel Coalition (TGC)

This essential reference teaches library staff how to handle the most common and confusing problems in serials cataloging by providing clear examples, practice exercises, and helpful advice based on experience. Serials cataloging can be an overwhelming task that frustrates even the most seasoned professional. This book provides simple guidance and real-world examples to illustrate best practices in serials cataloging. Demystifying Serials Cataloging: A Book of Examples is a reliable reference for learning how to catalog serials or improve cataloging skills. The book covers important elements of descriptive cataloging of serial publications such as explanations, sample records, applicable cataloging rules, and images of the serials. Examples demonstrate best practices and guidelines from the industry's leading cataloging standards including Anglo-American Cataloguing Rules: Second Revised Edition; CONSER Cataloging Manual; Library of Congress Rule Interpretation; and OCLC Bibliographic Formats and Standards. Each chapter contains helpful practice exercises to ensure understanding and reinforce learning.

An approachable guide to being a thoughtful, informed ally to disabled people, with actionable steps for what to say and do (and what not to do) and how you can help make the world a more inclusive place ONE OF THE BEST BOOKS OF THE YEAR: NPR, Booklist • “A candid, accessible cheat sheet for anyone who wants to thoughtfully join the conversation . . . Emily makes the intimidating approachable and the complicated clear.”—Rebekah Taussig, author of Sitting Pretty: The View from My Ordinary, Resilient, Disabled Body People with disabilities are the world’s largest minority, an estimated 15 percent of the global population. But many of us—disabled and nondisabled alike—don’t know how to act, what to say, or how to be an ally to the disability community. Demystifying Disability is a friendly handbook on the important disability issues you need to know about, including: • How to appropriately think, talk, and ask about disability • Recognizing and avoiding ableism (discrimination toward disabled people) • Practicing good disability etiquette • Ensuring accessibility becomes your standard practice, from everyday communication to planning special events • Appreciating disability history and identity • Identifying and speaking up about disability stereotypes in media Authored by celebrated disability rights advocate, speaker, and writer Emily Ladau, this practical, intersectional guide offers all readers a welcoming place to understand disability as part of the human experience. Praise for Demystifying Disability “Whether you have a disability, or you are non-disabled, Demystifying Disability is a MUST READ. Emily Ladau is a wise spirit who thinks deeply and writes exquisitely.”—Judy Heumann, international disability rights advocate and author of Being Heumann “Emily Ladau has done her homework, and Demystifying Disability is her candid, accessible cheat sheet for anyone who wants to thoughtfully join the conversation. A teacher who makes you forget you’re learning, Emily makes the intimidating approachable and the complicated clear. This book is a generous and needed gift.”—Rebekah Taussig, author of Sitting Pretty: The View from My Ordinary Resilient Disabled Body

Often referred to as the “black art” because of its complexity and uncertainty, software estimation is not as difficult or puzzling as people think. In fact, generating accurate estimates is straightforward—once you understand the art of creating them. In his highly anticipated book, acclaimed author Steve McConnell unravels the mystery to successful software estimation—distilling academic information and real-world experience into a practical guide for working software professionals. Instead of arcane treatises and rigid modeling techniques, this guide highlights a proven set of procedures, understandable formulas, and heuristics that individuals and development teams can apply to their projects to help achieve estimation proficiency. Discover how to: Estimate schedule and cost—or estimate the functionality that can be delivered within a given time frame Avoid common software estimation mistakes Learn estimation techniques for you, your team, and your organization * Estimate specific project activities—including development, management, and defect correction Apply estimation approaches to any type of project—small or large, agile or traditional Navigate the shark-infested political waters that surround project estimates When many corporate software projects are failing, McConnell shows you what works for successful software estimation.

This book presents a solid, research-based conceptual framework that demystifies organizational learning and bridges the gap between theory and practice. Using an integrative approach, authors Raanan Lipshitz, Victor Friedman and Micha Popper provide practitioners and researchers with tools for understanding organizational learning under real-world conditions.