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xiii | |
Preface |
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xvii | |
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PART 1 The Vision: The Digital Patient---Improving Research, Development, Education, and Healthcare Practice |
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1 | (48) |
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3 | (12) |
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4 | (1) |
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4 | (1) |
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5 | (1) |
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The Emergence of the Digital Patient |
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5 | (1) |
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6 | (2) |
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Enabling the Digital Patient |
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8 | (3) |
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11 | (1) |
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11 | (1) |
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12 | (3) |
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2 Reflecting on Discipulus and Remaining Challenges |
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15 | (12) |
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15 | (1) |
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A Brief Contextual Background and a Call for Integration: Personalized Medicine is Holistic |
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16 | (2) |
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The Many Versions of the Digital Patient: On the Road to Medical Avatars |
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18 | (1) |
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Discipulus: The Digital Patient Technological Challenges and Main Conclusions |
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19 | (5) |
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The Remaining Challenges and Big Data |
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24 | (1) |
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25 | (1) |
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26 | (1) |
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3 Advancing the Digital Patient |
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27 | (6) |
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27 | (1) |
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The Digital Patient: Its Early Start |
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28 | (2) |
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Engaging the Digital Patient |
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30 | (1) |
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31 | (2) |
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4 The Significance of Modeling and Visualization |
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33 | (16) |
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33 | (1) |
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Modeling a Complex System: Human Physiology |
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34 | (1) |
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Medical Modeling, Simulation, and Visualization |
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35 | (5) |
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Modes and Types of Visualization |
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40 | (3) |
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Visualization for Patient-Specific Usefulness |
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43 | (1) |
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43 | (2) |
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45 | (4) |
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PART 2 State of the Art: Systems Biology, the Physiome, and Personalized Health |
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49 | (158) |
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5 The Visible Human: A Graphical Interface for Holistic Modeling and Simulation |
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51 | (12) |
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51 | (2) |
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53 | (2) |
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55 | (1) |
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Virtual Reality Trainers and Simulators |
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56 | (2) |
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58 | (1) |
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59 | (4) |
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6 The Quantifiable Self: Petabyte by Petabyte |
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63 | (10) |
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63 | (1) |
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64 | (3) |
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Extending Smarr's Research |
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67 | (2) |
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The Quantified Self-Vision, Simplified |
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69 | (1) |
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69 | (2) |
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71 | (1) |
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72 | (1) |
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7 Systems Biology and Health Systems Complexity: Implications for the Digital Patient |
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73 | (12) |
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73 | (2) |
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75 | (1) |
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The Institute for Systems Biology |
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76 | (2) |
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78 | (3) |
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The Potential of Systems Biology |
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81 | (1) |
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82 | (1) |
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83 | (1) |
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83 | (2) |
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8 Personalized Computational Modeling for the Treatment of Cardiac Arrhythmias |
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85 | (16) |
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85 | (1) |
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Basics of Cardiac Electrophysiology |
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86 | (3) |
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Cardiac Modeling Advancements |
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89 | (1) |
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Regulation of Intracellular Calcium |
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90 | (1) |
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From Cells to Cables to Sheets to Tissue to the Heart |
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91 | (4) |
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Where Can we go from Here? What is the Cardiac Model in the Digital Patient? |
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95 | (1) |
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96 | (5) |
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9 The Physiome Project, openEHR Archetypes, and the Digital Patient |
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101 | (26) |
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101 | (1) |
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Multiscale Physiological Processes |
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102 | (1) |
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Physiome Project Standards, Repositories, and Tools |
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103 | (9) |
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112 | (1) |
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Archetype Definition Language |
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113 | (1) |
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Linking Archetypes to External Knowledge Sources (Terminology and Biomedical Ontologies) |
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114 | (1) |
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114 | (1) |
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OpenEHR Model Repository and Governance |
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115 | (1) |
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Fast Healthcare Interoperability Resources |
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115 | (1) |
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116 | (5) |
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121 | (1) |
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122 | (5) |
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10 Physics-Based Modeling for the Physiome |
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127 | (22) |
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127 | (1) |
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128 | (14) |
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142 | (1) |
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142 | (1) |
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143 | (1) |
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143 | (6) |
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11 Modeling and Understanding the Human Body with SwarmScript |
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149 | (22) |
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149 | (1) |
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150 | (2) |
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152 | (1) |
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Designing Interactive Agents |
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152 | (1) |
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153 | (1) |
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Answering Demand: The Design of SwarmScript |
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153 | (1) |
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Graph-Based Rule Representation |
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153 | (1) |
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The Source--Action--Target |
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154 | (1) |
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154 | (1) |
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155 | (9) |
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164 | (2) |
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166 | (1) |
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166 | (5) |
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12 Using Avatars and Agents to Promote Real-World Health Behavior Changes |
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171 | (10) |
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171 | (1) |
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172 | (1) |
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Using Agents and Avatars to Promote Health Behavior Changes |
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173 | (5) |
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178 | (1) |
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178 | (3) |
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13 Virtual Reality and Eating, Diabetes, and Obesity |
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181 | (18) |
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181 | (1) |
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181 | (5) |
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Obesity and Weight Stigma |
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186 | (1) |
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Virtual Reality as a Tool for Combatting Health Issues |
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187 | (4) |
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191 | (1) |
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191 | (8) |
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14 Immersive Virtual Reality to Model Physical: Social Interaction and Self-Representation |
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199 | (8) |
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199 | (1) |
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Theory for Immersive Virtual Learning Spaces |
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199 | (5) |
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204 | (1) |
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205 | (2) |
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PART 3 Challenges: Assimilating the Comprehensive Digital Patient |
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207 | (48) |
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15 A Roadmap for Building a Digital Patient System |
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209 | (16) |
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209 | (3) |
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212 | (1) |
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Building the Digital Patient Through Interoperability |
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213 | (9) |
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222 | (1) |
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223 | (1) |
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223 | (2) |
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16 Multidisciplinary, Interdisciplinary, and Transdisciplinary Research: Contextualization and Reliability of the Composite |
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225 | (16) |
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225 | (1) |
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Interdisciplinarity and Interdisciplinary Research |
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226 | (2) |
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Data Engineering to Support Interdisciplinarity and Interoperability |
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228 | (5) |
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Base Object Models to Support Transdisciplinarity and Composability |
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233 | (2) |
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Open Challenges on Reliability |
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235 | (2) |
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237 | (2) |
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239 | (2) |
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17 Bayes Net Modeling: The Means to Craft the Digital Patient |
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241 | (14) |
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241 | (5) |
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Other Interesting Applications |
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246 | (5) |
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251 | (2) |
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253 | (2) |
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PART 4 Potential Impact: Engaging The Digital Patient |
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255 | (50) |
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18 Virtual Reality Standardized Patients for Clinical Training |
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257 | (16) |
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257 | (1) |
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The Rationale for Virtual Standardized Patients |
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258 | (1) |
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Conversational Virtual Human Agents |
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259 | (1) |
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Usc Efforts to Create Virtual Standardized Patients |
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260 | (9) |
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269 | (1) |
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270 | (3) |
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19 The Digital Patient: Changing the Paradigm of Healthcare and Impacting Medical Research and Education |
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273 | (16) |
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273 | (2) |
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Overview Digital Medicine Projects |
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275 | (4) |
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Personalized Patient Care Clinical Use |
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279 | (2) |
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Recommended Education and Training for VPH Project Participation |
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281 | (3) |
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From Flexner to the 2010 Carnegie Report |
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284 | (2) |
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286 | (1) |
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287 | (2) |
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20 The Digital Patient: A Vision for Revolutionizing the Electronic Medical Record and Future Healthcare |
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289 | (10) |
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289 | (2) |
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Applications of the Digital Patient as the EMR |
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291 | (5) |
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296 | (1) |
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297 | (1) |
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297 | (2) |
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21 Realizing the Digital Patient |
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299 | (6) |
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Index |
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305 | |