Current and Future Application of Artificial Intelligence in Clinical Medicine

Table of Contents

Chapter 1 Artificial Intelligence (Ai) in Cancer Diagnosis and Prognosis
1. Introduction
2. Major Cancer Type
2.1. Lung Cancer
2.2. Breast Cancer
2.3. Prostate Cancer
2.4. Colorectal Cancer
2.5. Development in Diagnostic Tools
3. Artificial Intelligence (Ai) in Precision Medicine
4. Challenges for Ai in Cancer Treatment

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References

Chapter 2 Alternative or Auxiliary: Artificial Intelligence

• Accelerates the Development and Transformation of the Medical
• Care

1. Introduction
2. About Artificial Intelligence
3. Application Status and Development Prospects in the Medical

• Industry

3.1. Current Status of the Application of Ai
3.1.1. Intelligent Services in the Ageing Society
3.1.2. Smart Ward
3.1.3. Hazard Warning Identification
3.1.4. Assistance in Disease Diagnosis
3.1.5. Assistance in Drug Development and Disease Treatment
3.1.6. Gene Sequencing
3.2. Development Prospects of Ai
3.2.1. Cancer Management: The Combination of Tumor Organic Chips and Ai
3.2.2. Clinical Decision Support: Intelligent Data Integration
4. Thinking and Prospect

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References

Chapter 3 Rethinking Artificial Intelligence in China's COVID-19

• Pandemic

1. Introduction
2. the COVID-19 and Ai Application in China
2.1. Big Data, Population Management, and Transportation
2.2. Ai-Based Medical System Against COVID in China
2.3. Ai-Based Public Policy Against COVID-19 in China
2.4. Ai Enterprises and Societal Research and Development in China
3. Ai as a General-Purpose Technology of COVID-19 in China
4. Conclusion

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References

Chapter 4 Artificial Intelligence System and Its Application In

• Clinical Oncology

1. Introduction
2. Development of an Ai System
2.1. Establish a Knowledge Base
2.2. Building Knowledge Map
3. Man-Machine Communication Interface
4. Ai Clinical Validation
4.1. Phase I Clinical Research
4.2. Phase Ii Clinical Research
4.3. Phase Iii Clinical Research
4.4. Phase Iv Clinical Research

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References

Chapter 5 Current Medical Imaging and Artificial Intelligence and Its Future
1. Introduction
2. Process of Ai in Medical Imaging
2.1. Develop Standardized Use Cases
2.2. Establish a Data Sharing Method
2.3. Assess Clinical Practice and Infrastructure Needs
2.4. Ensure Technical Safety and Accuracy
3. Application of Ai + Medical Imaging in Various Fields
3.1. Lung Screening
3.2. Screening for Radiculopathy
3.3. Target Outline
3.4. Three-Dimensional Imaging of Viscera
3.5. Pathological Analysis
4. Ai and Its Applications in Eye Disease
5. Ai in Dentistry
5.1. the Rise of Machine Learning
5.2. the Future of Ai in Dentistry
6. Effects of Ai on Tumor Image Workflow
7. the Exploration and Development of Ai Image
7.1. Philips
7.2. Ali Health
7.3. Tencent Miying
7.4. Hainer Medical Trust
7.5. Deduce Technology
7.6. Yassen Technologies
7.7. Hui-Yi Hui Ying
7.8. Tuma Depth
7.9. Diyinjia
7.10. Heart Link Medical
7.11. Deepcare
7.12. Peptide Building Blocks
7.13. Smart Shadow Medical
7.14. Imagemesh Laboratory
8. the Next Frontier

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References

Chapter 6 Artificial Intelligence Played an Active Role in the COVID-

• 19 Epidemic in China
• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References

Chapter 7 Current Status and Future Outlook of Deep Learning

• Techniques for Nodule Detection

1. Introduction
2. Overview of Pulmonary Nodules
3. Overview of Ai and Deep Learning
4. Application of Deep Learning in Lung Nodules
4.1. Rationale for the Detection of Pulmonary Nodules
4.2. Application of Deep Learning in the Detection and Diagnosis of Pulmonary Nodules 90
5. Database
6. Issues and Outlook

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References

Chapter 8 Artificial Intelligence-Based Mining of Benign and Malignant Characteristics of Pulmonary Ground-Glass Nodules
1. Description of Ai
2. Definition and Classification of Ground-Glass Nodules
3. Analysis of Benign and Malignant Characteristics of Groundglass

• Nodules

3.1. Ct Value
3.2. Maximum Surface Area
3.3. Three-Dimensional Volume
3.4. Three-D Length to Diameter
3.5. Real Proportion
3.6. Doubling Time
3.7. Compactness and Sphericity Degree
4. Outlook and Progress

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• Abbreviation
• References

Chapter 9 Development of Artificial Intelligence in Imaging and Pathology
1. Introduction
2. Ai Imaging
2.1. Overview of Ai Imaging
2.2. Research Progress of Ai Imaging
3. Pathology
3.1. Exploration of Ai in Pathological Diagnosis
3.2. Grading of Renal Clear Cell Carcinoma
3. 3. Segmentation of Neoplastic Glandular Structure in Colorectal Cancer
3.4. Detection of Myco Bacterium Tuberculosis in Special Staining
3.5. Determination of Proliferating Cells in Cervical Epithelial Lesions
4. the Exploration of Ai in Tumor Prognostic Judgment
4.1. Prediction of Survival in Patients with Non-Small Cell Lung Cancer and Breast Cancer 115
4.2. Predicting Whether Patients with Stage T1 Colon Cancer Need Additional Radical

• Surgery

4.3. to Evaluate Postoperative Distant Metastasis in Patients with Esophageal Squamous

• Cell Carcinoma

5. Deep Learning in the Melanocyte Tumor Pathological Diagnosis 118
5.1. Deep Learning Development in Pathological Diagnosis
5.2. Diagnostic Melanocyte Benign and Malignant
5.3. Future Progress of Ai Diagnosis
6. Summary and Prospect

• Consent for Publication
• Conflict of Interest
• Acknowledgement
• References
• Subject Index

Author

• Shigao Huang
• Jie Yang