Intelligence-Based Healthcare: Artificial Intelligence Concepts with Real‑World Applications for Healthcare Leaders and Providers: Intelligence-Based Medicine: Subspecialty Series
Editat de Anthony Chang, Alfonso Limon, Gregg M. Gasconen Limba Engleză Paperback – oct 2026
- Insights from a senior chief intelligence officer with focus on machine and deep learning as well as related technologies, adoption strategies, and human elements in the era of AI.
- A balanced approach that connects AI concepts with real-world clinical applications in a non-technical, synergistic manner.
- Systematic presentation of case studies to help all stakeholders grasp the depth of AI thinking—making this a first-of-its-kind resource for transparency and relatability in healthcare AI.
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Specificații
ISBN-13: 9780443339332
ISBN-10: 0443339333
Pagini: 350
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Seria Intelligence-Based Medicine: Subspecialty Series
ISBN-10: 0443339333
Pagini: 350
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Seria Intelligence-Based Medicine: Subspecialty Series
Cuprins
Section I: Introduction to Artificial Intelligence
1. Artificial Intelligence in Healthcare
Section II: Data Science and Artificial Intelligence in Healthcare
2. Machine and Deep Learning Section III: Essential AI in Healthcare Topics
3. Ten Key Technologies in Healthcare AI
4. Ten Essential Dimensions in Healthcare AI
5. Ten Human-Related Topics in the Era of AI
6. AI in Healthcare: Lessons Learned and Future Trends
Section IV: AI in Healthcare Resources
7. Organizational AI Readiness Assessment
Section V: AI in Healthcare Case Applications
8. Case Study 1: Addressing Organizational Structures to Deploy an AI-Ready, Enterprise Scale Data Architecture
9. Case Study 2: Implementing Machine Learned Algorithms to Predict Patient Deterioration in Hospital
10. Case Study 3: Artificial Intelligence Applications for the Prevention, Diagnosis, and Management of Intraoperative Hypotension
11. Case Study 4: A Machine Learning-Based Risk Calculator for Personalized BPD Care: Predicting Readmission Risk
12. Case Study 5: Clinical Documentation Improvements Following Introduction of AI-Enabled Software
13. Case Study 6: Development, Deployment, and Maintenance of a Tool for Predicting Hospital Inpatient Census
14. Case Study 7: Supply-Eye: AI System that Automates the Tracking of Clinical Supplies Usage and Reordering
15. Case Study 8: Accuracy Improvement through the Development and Implementation of an Artificial Intelligence-Enabled Insurance Verification System
16. Case Study 9: Predicting Extubation Success in Patients with Established Bronchopulmonary Dysplasia
17. Case Study 10: Stroke Treatment and Outcomes at a Comprehensive Stroke Center Before and After Automated Emergent Large Vessel Occlusion Detection by Artificial Intelligence
18. Case Study 11: Refocusing Predictive Modeling on Diagnostic Decision-Making Support
19. Case Study 12: Leveraging a Large Language Model to Provide Clinical Documentation, Coding, and Quality Metric Extraction at Scale in Emergency Departments and Urgent Care
20. Case Study 13: Audio and Immersion – Text-to-Speech within Immersive Healthcare
21. Case Study 14: Deploying Ambient AI Scribes to Enhance Clinical Documentation and Reduce Provider Burnout
22. Case Study 15: Distributed Multi-Agent AI Application for Clinical Trial Recruiting
23. Case Study 16: Agentic AI with Practical Healthcare Applications
24. Case Study 17: Evaluation of Artificial Intelligence’s Impact on Patient Outcomes: The CLOT (Children’s Likelihood Of Thrombosis) Demonstration Project
1. Artificial Intelligence in Healthcare
Section II: Data Science and Artificial Intelligence in Healthcare
2. Machine and Deep Learning Section III: Essential AI in Healthcare Topics
3. Ten Key Technologies in Healthcare AI
4. Ten Essential Dimensions in Healthcare AI
5. Ten Human-Related Topics in the Era of AI
6. AI in Healthcare: Lessons Learned and Future Trends
Section IV: AI in Healthcare Resources
7. Organizational AI Readiness Assessment
Section V: AI in Healthcare Case Applications
8. Case Study 1: Addressing Organizational Structures to Deploy an AI-Ready, Enterprise Scale Data Architecture
9. Case Study 2: Implementing Machine Learned Algorithms to Predict Patient Deterioration in Hospital
10. Case Study 3: Artificial Intelligence Applications for the Prevention, Diagnosis, and Management of Intraoperative Hypotension
11. Case Study 4: A Machine Learning-Based Risk Calculator for Personalized BPD Care: Predicting Readmission Risk
12. Case Study 5: Clinical Documentation Improvements Following Introduction of AI-Enabled Software
13. Case Study 6: Development, Deployment, and Maintenance of a Tool for Predicting Hospital Inpatient Census
14. Case Study 7: Supply-Eye: AI System that Automates the Tracking of Clinical Supplies Usage and Reordering
15. Case Study 8: Accuracy Improvement through the Development and Implementation of an Artificial Intelligence-Enabled Insurance Verification System
16. Case Study 9: Predicting Extubation Success in Patients with Established Bronchopulmonary Dysplasia
17. Case Study 10: Stroke Treatment and Outcomes at a Comprehensive Stroke Center Before and After Automated Emergent Large Vessel Occlusion Detection by Artificial Intelligence
18. Case Study 11: Refocusing Predictive Modeling on Diagnostic Decision-Making Support
19. Case Study 12: Leveraging a Large Language Model to Provide Clinical Documentation, Coding, and Quality Metric Extraction at Scale in Emergency Departments and Urgent Care
20. Case Study 13: Audio and Immersion – Text-to-Speech within Immersive Healthcare
21. Case Study 14: Deploying Ambient AI Scribes to Enhance Clinical Documentation and Reduce Provider Burnout
22. Case Study 15: Distributed Multi-Agent AI Application for Clinical Trial Recruiting
23. Case Study 16: Agentic AI with Practical Healthcare Applications
24. Case Study 17: Evaluation of Artificial Intelligence’s Impact on Patient Outcomes: The CLOT (Children’s Likelihood Of Thrombosis) Demonstration Project