Current and Future Application of Artificial Intelligence in Clinical Medicine.

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Place / Publishing House:Sharjah : : Bentham Science Publishers,, 2021.
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spelling Huang, Shigao.
Current and Future Application of Artificial Intelligence in Clinical Medicine.
1st ed.
Sharjah : Bentham Science Publishers, 2021.
Ã2021.
1 online resource (154 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Cover -- Title -- Copyright -- End User License Agreement -- Contents -- Preface -- Acknowledgements -- List of Contributors -- Artificial Intelligence (AI) in Cancer Diagnosis and Prognosis -- Parsa Mahmood Dar1,*, Amara Dar2 and Komal Hayat3 -- 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 -- Alternative or Auxiliary: Artificial Intelligence Accelerates the Development and Transformation of the Medical Care -- Jie Yang1,2,*, Quanyi Hu1, Rui Tang3, Han Wang4,5, Kairong Duan1,6, Feng Wu5 and Simon Fong1,5 -- 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 -- Rethinking Artificial Intelligence in China's COVID-19 Pandemic -- Qichao Wang1,* -- 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 -- Artificial Intelligence System and its Application in Clinical Oncology -- Shigao Huang1,*, Jie Yang2,3, Qun Song2, Kexing Liu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- Current Medical Imaging and Artificial Intelligence and its Future -- Shigao Huang1, Jie Yang2,3, Lijian Tan3, Simon Fong2,4 and Qi Zhao1 -- 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 -- Artificial Intelligence Played an Active Role in the COVID-19 Epidemic in China -- Shigao Huang1,*, Jie Yang2,3,4, Xianxian Liu2, Simon Fong2,4 and Qi Zhao1 -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Current Status and Future Outlook of Deep Learning Techniques For Nodule Detection -- Shigao Huang1,*, Jie Yang2,3,4, Kun Lan2, Sunny Yaoyang Wu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- 5. DATABASE -- 6. ISSUES AND OUTLOOK -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Artificial Intelligence-Based Mining of Benign and Malignant Characteristics of Pulmonary Ground-Glass Nodules -- Xiaoxia Li1, Ting Gao2 and Shigao Huang3,* -- 1. DESCRIPTION OF AI -- 2. DEFINITION AND CLASSIFICATION OF GROUND-GLASS NODULES -- 3. ANALYSIS OF BENIGN AND MALIGNANT CHARACTERISTICS OF GROUND-GLASS 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 -- Development of Artificial Intelligence in Imaging and Pathology -- Gang Liu1 and Tao Qi2,* -- 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 -- 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 -- 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 -- Back Cover.
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Artificial intelligence--Medical applications.
Electronic books.
Yang, Jie.
Print version: Huang, Shigao Current and Future Application of Artificial Intelligence in Clinical Medicine Sharjah : Bentham Science Publishers,c2021 9781681088426
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author Huang, Shigao.
spellingShingle Huang, Shigao.
Current and Future Application of Artificial Intelligence in Clinical Medicine.
Cover -- Title -- Copyright -- End User License Agreement -- Contents -- Preface -- Acknowledgements -- List of Contributors -- Artificial Intelligence (AI) in Cancer Diagnosis and Prognosis -- Parsa Mahmood Dar1,*, Amara Dar2 and Komal Hayat3 -- 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 -- Alternative or Auxiliary: Artificial Intelligence Accelerates the Development and Transformation of the Medical Care -- Jie Yang1,2,*, Quanyi Hu1, Rui Tang3, Han Wang4,5, Kairong Duan1,6, Feng Wu5 and Simon Fong1,5 -- 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 -- Rethinking Artificial Intelligence in China's COVID-19 Pandemic -- Qichao Wang1,* -- 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 -- Artificial Intelligence System and its Application in Clinical Oncology -- Shigao Huang1,*, Jie Yang2,3, Qun Song2, Kexing Liu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- Current Medical Imaging and Artificial Intelligence and its Future -- Shigao Huang1, Jie Yang2,3, Lijian Tan3, Simon Fong2,4 and Qi Zhao1 -- 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 -- Artificial Intelligence Played an Active Role in the COVID-19 Epidemic in China -- Shigao Huang1,*, Jie Yang2,3,4, Xianxian Liu2, Simon Fong2,4 and Qi Zhao1 -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Current Status and Future Outlook of Deep Learning Techniques For Nodule Detection -- Shigao Huang1,*, Jie Yang2,3,4, Kun Lan2, Sunny Yaoyang Wu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- 5. DATABASE -- 6. ISSUES AND OUTLOOK -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Artificial Intelligence-Based Mining of Benign and Malignant Characteristics of Pulmonary Ground-Glass Nodules -- Xiaoxia Li1, Ting Gao2 and Shigao Huang3,* -- 1. DESCRIPTION OF AI -- 2. DEFINITION AND CLASSIFICATION OF GROUND-GLASS NODULES -- 3. ANALYSIS OF BENIGN AND MALIGNANT CHARACTERISTICS OF GROUND-GLASS 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 -- Development of Artificial Intelligence in Imaging and Pathology -- Gang Liu1 and Tao Qi2,* -- 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 -- 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 -- 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 -- Back Cover.
author_facet Huang, Shigao.
Yang, Jie.
author_variant s h sh
author2 Yang, Jie.
author2_variant j y jy
author2_role TeilnehmendeR
author_sort Huang, Shigao.
title Current and Future Application of Artificial Intelligence in Clinical Medicine.
title_full Current and Future Application of Artificial Intelligence in Clinical Medicine.
title_fullStr Current and Future Application of Artificial Intelligence in Clinical Medicine.
title_full_unstemmed Current and Future Application of Artificial Intelligence in Clinical Medicine.
title_auth Current and Future Application of Artificial Intelligence in Clinical Medicine.
title_new Current and Future Application of Artificial Intelligence in Clinical Medicine.
title_sort current and future application of artificial intelligence in clinical medicine.
publisher Bentham Science Publishers,
publishDate 2021
physical 1 online resource (154 pages)
edition 1st ed.
contents Cover -- Title -- Copyright -- End User License Agreement -- Contents -- Preface -- Acknowledgements -- List of Contributors -- Artificial Intelligence (AI) in Cancer Diagnosis and Prognosis -- Parsa Mahmood Dar1,*, Amara Dar2 and Komal Hayat3 -- 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 -- Alternative or Auxiliary: Artificial Intelligence Accelerates the Development and Transformation of the Medical Care -- Jie Yang1,2,*, Quanyi Hu1, Rui Tang3, Han Wang4,5, Kairong Duan1,6, Feng Wu5 and Simon Fong1,5 -- 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 -- Rethinking Artificial Intelligence in China's COVID-19 Pandemic -- Qichao Wang1,* -- 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 -- Artificial Intelligence System and its Application in Clinical Oncology -- Shigao Huang1,*, Jie Yang2,3, Qun Song2, Kexing Liu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- Current Medical Imaging and Artificial Intelligence and its Future -- Shigao Huang1, Jie Yang2,3, Lijian Tan3, Simon Fong2,4 and Qi Zhao1 -- 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 -- Artificial Intelligence Played an Active Role in the COVID-19 Epidemic in China -- Shigao Huang1,*, Jie Yang2,3,4, Xianxian Liu2, Simon Fong2,4 and Qi Zhao1 -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Current Status and Future Outlook of Deep Learning Techniques For Nodule Detection -- Shigao Huang1,*, Jie Yang2,3,4, Kun Lan2, Sunny Yaoyang Wu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- 5. DATABASE -- 6. ISSUES AND OUTLOOK -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Artificial Intelligence-Based Mining of Benign and Malignant Characteristics of Pulmonary Ground-Glass Nodules -- Xiaoxia Li1, Ting Gao2 and Shigao Huang3,* -- 1. DESCRIPTION OF AI -- 2. DEFINITION AND CLASSIFICATION OF GROUND-GLASS NODULES -- 3. ANALYSIS OF BENIGN AND MALIGNANT CHARACTERISTICS OF GROUND-GLASS 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 -- Development of Artificial Intelligence in Imaging and Pathology -- Gang Liu1 and Tao Qi2,* -- 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 -- 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 -- 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 -- Back Cover.
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fullrecord <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>08363nam a22004453i 4500</leader><controlfield tag="001">5006676565</controlfield><controlfield tag="003">MiAaPQ</controlfield><controlfield tag="005">20240229073842.0</controlfield><controlfield tag="006">m o d | </controlfield><controlfield tag="007">cr cnu||||||||</controlfield><controlfield tag="008">240229s2021 xx o ||||0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781681088419</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781681088426</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(MiAaPQ)5006676565</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(Au-PeEL)EBL6676565</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1260346638</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">MiAaPQ</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">MiAaPQ</subfield><subfield code="d">MiAaPQ</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">R859.7.A78</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">610.285</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Huang, Shigao.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Current and Future Application of Artificial Intelligence in Clinical Medicine.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Sharjah :</subfield><subfield code="b">Bentham Science Publishers,</subfield><subfield code="c">2021.</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">Ã2021.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (154 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Cover -- Title -- Copyright -- End User License Agreement -- Contents -- Preface -- Acknowledgements -- List of Contributors -- Artificial Intelligence (AI) in Cancer Diagnosis and Prognosis -- Parsa Mahmood Dar1,*, Amara Dar2 and Komal Hayat3 -- 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 -- Alternative or Auxiliary: Artificial Intelligence Accelerates the Development and Transformation of the Medical Care -- Jie Yang1,2,*, Quanyi Hu1, Rui Tang3, Han Wang4,5, Kairong Duan1,6, Feng Wu5 and Simon Fong1,5 -- 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 -- Rethinking Artificial Intelligence in China's COVID-19 Pandemic -- Qichao Wang1,* -- 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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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 -- Artificial Intelligence System and its Application in Clinical Oncology -- Shigao Huang1,*, Jie Yang2,3, Qun Song2, Kexing Liu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- Current Medical Imaging and Artificial Intelligence and its Future -- Shigao Huang1, Jie Yang2,3, Lijian Tan3, Simon Fong2,4 and Qi Zhao1 -- 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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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 -- Artificial Intelligence Played an Active Role in the COVID-19 Epidemic in China -- Shigao Huang1,*, Jie Yang2,3,4, Xianxian Liu2, Simon Fong2,4 and Qi Zhao1 -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Current Status and Future Outlook of Deep Learning Techniques For Nodule Detection -- Shigao Huang1,*, Jie Yang2,3,4, Kun Lan2, Sunny Yaoyang Wu2, Simon Fong2,4 and Qi Zhao1 -- 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 -- 5. DATABASE -- 6. ISSUES AND OUTLOOK -- CONSENT FOR PUBLICATION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENT -- REFERENCES -- Artificial Intelligence-Based Mining of Benign and Malignant Characteristics of Pulmonary Ground-Glass Nodules -- Xiaoxia Li1, Ting Gao2 and Shigao Huang3,* -- 1. DESCRIPTION OF AI -- 2. DEFINITION AND CLASSIFICATION OF GROUND-GLASS NODULES -- 3. ANALYSIS OF BENIGN AND MALIGNANT CHARACTERISTICS OF GROUND-GLASS 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 -- Development of Artificial Intelligence in Imaging and Pathology -- Gang Liu1 and Tao Qi2,* -- 1. INTRODUCTION -- 2. AI IMAGING -- 2.1. Overview of AI Imaging.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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 -- 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 -- 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 -- Back Cover.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources.</subfield></datafield><datafield tag="590" ind1=" " ind2=" "><subfield code="a">Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. </subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Artificial intelligence--Medical applications.</subfield></datafield><datafield tag="655" ind1=" " ind2="4"><subfield code="a">Electronic books.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yang, Jie.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="a">Huang, Shigao</subfield><subfield code="t">Current and Future Application of Artificial Intelligence in Clinical Medicine</subfield><subfield code="d">Sharjah : Bentham Science Publishers,c2021</subfield><subfield code="z">9781681088426</subfield></datafield><datafield tag="797" ind1="2" ind2=" "><subfield code="a">ProQuest (Firm)</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=6676565</subfield><subfield code="z">Click to View</subfield></datafield></record></collection>