≫

Artificial Intelligence: Applications in Healthcare Delivery

Algorithmic Medicine Introduction Al in Medicine - A History Al Types and Applications Computer Vision Natural Language Processing Robotics Challenges and Solutions The Future References Use of Artificial Intelligence in the Screening and Treatment of Chronic Diseases Introduction Role of Artificial Intelligence in Chronic Disease Machine Learning in Diabetes Prediction and Diagnosis of Type 2 Diabetes Blood Glucose Management Diabetes Phenotyping Early Detection of Diabetes Complications Machine Learning in Cardiovascular Disease Cardiovascular Risk Prediction Identification of Novel Cardiovascular Disease Phenotypes ECG and Diagnostic Accuracy Improvement Imaging and Diagnostic Accuracy Improvement Machine Learning in Dementia Early Dementia Prediction Dementia Phenotyping Challenges in the Implementation of Al in Chronic Disease Management Methodical Challenges Practical Challenges Solutions Real-Life Clinical Practice Applicability Conclusions References Al and Drug Discovery Introduction High-Throughput Screening (HTS)Virtual Screening (VS)Fingerprint-Based Virtual Screening Automatic Feature Extraction via Deep Learning Deep Learning-Based Virtual Screening Successful Examples The Impact of Al in Drug Discovery,Future Perspective References Mammographic Screening and Breast Cancer Management - Part 1 Introduction Breast Cancer Mammography and Population Screening Artificial Intelligence and Mammography History of Computer-Aided Mammographic Screening Deep Learning for Screening Mammography Current State of the Art Triage Cancer Detection Density and Cancer Risk Challenges and Future Possibilities Prognosis and Treatment Response Differentiating Ductal Carcinoma In Situ and Invasive Breast Cancer Al for Breast Cancer Care Multi-Institutional Model Training Interpretability References Mammographic Screening and Breast Cancer Management - Part 2 Introduction Al-Enabled CAD ProFound Al Other Al Applications Conclusion References Deep Learning for Drawing Insights from Patient Data for Diagnosis and Treatment Introduction Convolutional Neural Networks Skin Lesion Classification Problem The HAM10000 Image-Based Skin Cancer Dataset and Its Characteristics CNN Approaches to Skin Cancer Classification Using Pre-Trained Model and Freezing Its Weights End-to-End Training Using Pre-Trained Model Weights Transfer Learning on HAM10000 Dataset Pre-Processing HAM10000 Dataset Establishing Train and Test Sets Data Augmentation VGG16 Model for HAM10000 Dataset Model Training Preliminary Results Deployment on Smart Phones Conclusion and Future Directions References A Simple and Replicable Framework for the Implementation of Clinical Data Science Background/lntroduction What Is the Problem with Clinical Data Analysis in Oncology?Lack of a Framework in the Hospital Setting Nature and Governance of Oncological Clinical Data Methods Selection of a Concrete and Relevant Clinical Problem Problem Understanding Framework Proposal Framework Implementation Framework Application Results Proposed Framework Oncological Electronic Medical Record (OEMR)Oncological Data Model (ODM)Clinical Data Analysis (CDA)Outcomes/lmpact on Healthcare Delivery References Clinical Artificial Intelligence -Technology Application or Change Management?Introduction Methods Recruitment and Consent Data Collection Tools Data Collection Process Results GPs Evaluation of Risk Algorithm: Qualitative Accuracy Usability Suggestions for Improvement Discussion Decision Support Regulation Ethics Legal Quality of Data New Clinical Methods Conclusion Acknowledgment References Impacting Perioperative Quality and Patient Safety Using Artificial Intelligence Introduction Quality Measurement-Cohort and Performance Analysis Predictive Analytics Diagnosis and Image Analysis Decision Support Therapeutics Future Prospects References Application of an Intelligent Stochastic Optimization Nonlinear Model Introduction Stochastic Optimization Models for Locating Ambulances Stochastic Optimization Model Conclusions Acknowledgments References Audit of Artificial Intelligence Algorithms and Its Impact in Relieving Shortage of Specialist Doctors Introduction Radiology in India Technological Advances in Radiology Use-Cases Automated Chest X-Ray Reporting Using Al Normal vs. Abnormal Chest X-Ray Classification Automated Diagnosis of Tuberculosis on Chest X-Ray Al as a Quality Assessment Tool Automated Head CT Reporting in Emergencies Chest CT Screening Using Al Audit Algorithmic Audit Independent Validation Stratification of Data for Audit The Far North and Far South Cases Real-World Deployment and Testing Improving the Algorithm More Power to Clinicians References Knowledge Management in a Learning Health System Introduction History Current Practice Cost of Generating New Knowledge Time Inefficiency of Generating New Knowledge A Learning Healthcare System Clinical Knowledge Management Business Model of Healthcare Conclusion References Transfer Learning to Enhance Amenorrhea Status Prediction in Cancer and Fertility Data with Missing Values Introduction Related Work Amenorrhoea Status Prediction Missing Value Imputation Transfer Learning CCA-Based Transfer Learning Standard Linear CCA with Regularization Kernel CCA Deep CCA Method Unified Feature Representation with Imputation Nearest Pairing Methods CCA Transformation Experiments and Result Data Description Result Distance Metrics Evaluation Proxy-A-Distance Maximum Mean Discrepancy Coral Loss Function Prediction Accuracy Discussion Conclusion Acknowledgement References AMD Severity Prediction and Explainability Using Image Registration and Deep Embedded Clustering Introduction Method Atlas Construction Using Groupwise Registration Deep Embedded Clustering Network Estimation of Registration Parameters Training Stage Implementation Predicting Severity of Test Image Experimental Results Registration Results Classification Results Identification of Disease Subgroups and Explainability Conclusion References Application of Artificial Intelligence in Thyroidology Introduction Ultrasound Image Classification Applications in Cytopathology Molecular Diagnosis Wearables Generative Adversarial Networks Discussion References Use of Artificial Intelligence in Sepsis Detection and Management Background Sepsis Prediction Sepsis Detection Sepsis Treatment Sepsis Outcome Conclusion References Transforming Clinical Trials with Artificial Intelligence Introduction Patient Recruitment for Clinical Trials Patient Selection for Clinical Trials Synthetic Data in Clinical Trials Trials for Precision Medicine Conclusion References An Industry Review of Neuromorphic Chips Introduction Overview of Al Al-Chips IBM Google NVIDIA Google and Microsoft's Collaboration with Al Chips Huawei Microsoft Intel Apple General Vision BrainScaleS APT Group Application in Healthcare References Artificial Empathy - An Artificial Intelligence Challenge Introduction Empathy Enabling Empathy with Al Challenges Future Direction Conclusion References

Next chapter

Algorithmic Medicine