AI in Healthcare

AI in Healthcare

How Artificial Intelligence Is Changing IT Operations and Infrastructure Services
1. Aufl.

von: Robert Shimonski

38,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 23.12.2020
ISBN/EAN: 9781119680055
Sprache: englisch
Anzahl Seiten: 288

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.


<p><b>The best source for cutting-edge insights into AI in healthcare operations</b></p> <p><i>AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services</i> collects, organizes and provides the latest, most up-to-date research on the emerging technology of artificial intelligence as it is applied to healthcare operations.</p> <p>Written by a world-leading technology executive specializing in healthcare IT, this book provides concrete examples and practical advice on how to deploy artificial intelligence solutions in your healthcare environment. <i>AI in Healthcare</i> reveals to readers how they can take advantage of connecting real-time event correlation and response automation to minimize IT disruptions in critical healthcare IT functions.</p> <p>This book provides in-depth coverage of all the most important and central topics in the healthcare applications of artificial intelligence, including:</p> <ul> <li>Healthcare IT</li> <li>AI Clinical Operations</li> <li>AI Operational Infrastructure</li> <li>Project Planning</li> <li>Metrics, Reporting, and Service Performance</li> <li>AIOps in Automation</li> <li>AIOps Cloud Operations</li> <li>Future of AI</li> </ul> <p>Written in an accessible and straightforward style, this book will be invaluable to IT managers, administrators, and engineers in healthcare settings, as well as anyone with an interest or stake in healthcare technology.</p>
<p>Introduction xvii</p> <p><b>Chapter 1 Healthcare IT and the Growing Need for AI Operations 1</b></p> <p>A Brief History of AI and Healthcare 3</p> <p>Healthcare IT Expansion and Growth 4</p> <p>Data Overload 5</p> <p>Digital Transformation of Healthcare 7</p> <p>The Science of Healthcare Innovation 9</p> <p>Artificial Intelligence in Healthcare 10</p> <p>Healthcare IT Operations 14</p> <p>AIOps Platform Strategy 18</p> <p>Platform Types 19</p> <p>Customer Experience and AIOps 20</p> <p>AIOps Considerations and Goals 22</p> <p>Summary 23</p> <p><b>Chapter 2 AI Healthcare Operations (Clinical) 25</b></p> <p>Clinical Impact of AIOps 26</p> <p>Gaining a Competitive Edge with Intelligent Cloud, Data Analytics, and AI 27</p> <p>Design and Innovation 29</p> <p>AIOps for Healthcare Delivery 33</p> <p>AIOps for Service Performance 38</p> <p>Clinical AI, AIOps, and Future Platform Convergence 39</p> <p>Security and Privacy 41</p> <p>Why Security is Paramount in AIOps 41</p> <p>HIPAA, PHI, and PII Protection 43</p> <p>Summary 45</p> <p><b>Chapter 3 AI Healthcare Operations (Operational Infrastructure) 47</b></p> <p>Getting Started with AIOps 48</p> <p>Strategy of AIOps Deployments 50</p> <p>Creating a Scope 51</p> <p>AIOps Platforms, Products, and Services Selection 54</p> <p>AIOps Product Selection: General Topics 54</p> <p>Product Review: AIOps Tool Splunk 57</p> <p>Product Review: AIOps Tool ServiceNow 60</p> <p>Product Review: AIOps Tool Dynatrace 64</p> <p>Workflow and Event Management Design 67</p> <p>Service Design with AIOps 67</p> <p>Day-to-Day Operational Management 69</p> <p>Summary 70</p> <p><b>Chapter 4 Project Planning for AIOps 73</b></p> <p>Project Planning Requirements 74</p> <p>Assigning a Project Manager 75</p> <p>Creating a Project Plan 77</p> <p>Building the Project Plan 78</p> <p>Planning a Healthcare System Project 83</p> <p>Deploying AIOps 85</p> <p>Deploying AIOps into the Environment 86</p> <p>Configuring AIOps in the Environment 88</p> <p>Summary 91</p> <p><b>Chapter 5 Using AI for Metrics, Performance, and Reporting 93</b></p> <p>System Performance Metrics 94</p> <p>Information Technology Metrics 94</p> <p>Using AI for Metrics, Performance, and Reporting 98</p> <p>Strategy and Goals for AI Deployment 101</p> <p>Benefits of Healthcare AIOps Service Performance Reporting 102</p> <p>Developing Usable AIOps Metrics 104</p> <p>Helpful Tools You Can Use 105</p> <p>Gathering Usable Metrics 107</p> <p>Using Dynatrace 108</p> <p>Using Splunk 110</p> <p>Using ServiceNow 117</p> <p>Clinical and IT Metrics and Collective Actions 123</p> <p>Usable Healthcare AIOps Dashboards 127</p> <p>Summary 128</p> <p><b>Chapter 6 AIOps and Automation in Healthcare Operations 131</b></p> <p>Automation, Workflow, Process, and Intelligence Design 132</p> <p>Designing the Framework for Automation 132</p> <p>Understanding Automation 133</p> <p>Improved User Experience 134</p> <p>Designing Workflow and Process Engineering 135</p> <p>Quality Control and Assurance 138</p> <p>Foundational and Required Design Items 139</p> <p>Configuring and Using AIOps Automation 146</p> <p>Monitoring and Operating Event Management Services 148</p> <p>Creating and Realizing Automation, ML, and AI 152</p> <p>Automating Splunk and IT Service Analyzer 155</p> <p>Splunk IT Service Intelligence 160</p> <p>When Should You Use AI and ML? 162</p> <p>Summary 163</p> <p><b>Chapter 7 Cloud Operations and AIOps 165</b></p> <p>Understanding the Cloud 166</p> <p>Understanding Cloud Computing 166</p> <p>Cloud as a Service 172</p> <p>Hybrid Cloud Solutions 175</p> <p>When You Should (and Shouldn’t) Consider the Cloud 178</p> <p>Deploying to the Cloud 179</p> <p>Conducting a Request for Proposal 182</p> <p>Additional Deployment Options 184</p> <p>Managing in the Cloud 186</p> <p>Cloud Management and Monitoring Solutions 189</p> <p>Summary 191</p> <p><b>Chapter 8 The Future of Healthcare AI 193</b></p> <p>The Dynamically Changing World of AI 194</p> <p>The Future of AI 198</p> <p>Artificial Intelligence and Healthcare Innovation 201</p> <p>Big Data, DataOps, Analytics, and Informatics 201</p> <p>Telehealth (Telemedicine) 204</p> <p>Telehealth Innovations 206</p> <p>Telehealth AI 209</p> <p>Future Innovation Merging Clinical and IT Operations 212</p> <p>The Future and Beyond 214</p> <p>AIOps, the Cloud, and Security 218</p> <p>Summary 218</p> <p><b>Chapter 9 The Convergence of Healthcare AI Technology 221</b></p> <p>Overview of Convergence 222</p> <p>Systems Integration 225</p> <p>Convergence of AI, HIT, and HIE 228</p> <p>IoT and AI 230</p> <p>IoT Management 237</p> <p>AIOps Management and Security 239</p> <p>Summary 245</p> <p>Appendix Sample AIOps Use Cases and Examples 247</p> <p>Index 259</p>
<p><b>ROB SHIMONSKI</b> is a technology executive specializing in healthcare IT for Northwell Health, one of the largest health systems in America. He is responsible for modernizing operational support with new technologies like cloud computing and storage and artificial intelligence. He currently focuses on AI Operations. He has written more than 20 books on IT topics, including penetration testing, incident handling, and cyberwarfare.
<p><b>Discover how you can use AI to effect dramatic changes in your healthcare organization today</b> <p>In <i>AI in Healthcare: How Artificial Intelligence Is Changing IT Operations and Infrastructure Services,</i> author and health IT expert Robert Shimonski delivers a cutting-edge and comprehensive treatment of the intersection of artificial intelligence and operations (AIOps). He describes how the integration of real-time event correlation and response automation helps to minimize disruptions in mission-critical IT functions in healthcare organizations. <p>Through the book's practical examples and accessible advice, you'll learn about how both patients and clinicians experience better outcomes through the implementation of AI in healthcare IT systems. You'll also discover how to use AI to deliver the intelligence you need to continuously access accurate healthcare data, eliminate downtime, and reduce negative interactions patients and clinicians have with your organization's technology. <p><i>AI in Healthcare</i> explains, in straightforward terms, why healthcare systems, networks, data, and critical infrastructures must all be more efficient, self-aware, and "self-healing" than they were in the past, and how you can achieve that goal. By focusing on the tools, systems, and services made possible by AI rather than on their underlying mathematics, the book allows a non-technical audience to quickly make the right decisions regarding the selection and deployment of optimal solutions. <p>Perfect for IT managers, administrators, and engineers at healthcare organizations, <i>AI in Healthcare</i> also belongs on the bookshelves of C-level executives, informatics specialists, and business analysts who seek to improve the performance of their own firms. Finally, virtually anyone involved in an operational role in a healthcare organization will benefit from the author's treatment of subjects like: <ul> <li><b>An introduction to healthcare IT and the rapidly growing need for AI</b></li> <li><b>Clinical healthcare artificial intelligence operations, including descriptions of Big Data and informatics</b></li> <li><b>AI healthcare operations and operational infrastructure and how to select an appropriate operations software suite</b></li> <li><b>Project planning and management in the deployment of AI solutions in the healthcare environment</b></li> </ul>

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