Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem

The book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies. It includes current developments for future directions as well as covering the concept of the healthcare system along with its ecosystem.

Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem focuses on the mechanisms of proposing and incorporating solutions along with architectural concepts, design principles, smart solutions, decision-making process, and intelligent predictions. It offers state-of-the-art approaches for overall innovations, developments, and implementation of the smart healthcare ecosystem and highlights medical signal and image processing algorithms, healthcare-based computer vision systems, and discusses explainable AI (XAI) techniques for healthcare.

This book will be useful to researchers involved in AI, IoT, Data, and emerging technologies in the medical industry. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

1. Electronic Health Records Security and Privacy Enhancement using Blockchain Technology. 2. Internet of Medical Things (IoMT) Driving the Digital Transformation of the Healthcare Sector. 3. AI-enabled Solution - A Game Changer for Private Healthcare Providers. 4. The Analytics of Hospitality of Hospitals in Healthcare Ecosystem. 5. Deep Transfer-Learning Model for COVID-19 Diagnosis with Feature Extraction-based SVM and KNN Classifiers. 6. Heart Disease Prediction using Logistic Regression and Random Forest Classifier. 7. Convolutional Neural Network Based Smart Incubator System for Infant Monitoring using IoT Technology. 8. A Fuzzy Expert System for Alzheimer's Disease Diagnosis Using 2D Wavelet Texture Biomarkers. 9. Application of Machine Learning Algorithms in Diabetes Prediction. 10. An Improved Random Forest Model for Detecting Heart Disease. 11. A Hybrid Feature Selection and Stacked Generalization Model to Detect Breast Cancer. 12. Hepatocellular Carcinoma Patients Survival Forecasting Model Using Ensemble Learning Approach. 13. Heart Disease and Liver Disease Prediction using Machine Learning. 14. A Novel Improved Logistic Regression Model for Diagnosing Heart Disease. 15. Systematic Review: An Early Detection of Skin Disease using Machine Learning. 16. Hospital Performance Management: Implementation of Real-Time Monitoring System for Clinical and Administration Team. 17. Simplified Hospital Management System: Robotic Process Automation (RPA) to Rescue. 18. Methodological and Analytical Considerations for Development and Implementation of an Audit System for Telemedicine. 19. Hospital 4.0: Capitalization of Health and Healthcare in Industry 4.0 Economy. 20. Use of Technology for Monitoring the Immunization Status of Children Aged Five Years. 21. Intelligent Handy Healthcare System in Medical Ecosystem.

Dr. Alex Khang, is a professor in information technology at the Universities of Science and Technology in Vietnam, India, and United States; AI and data scientist, software industry expert, and the chief of technology officer (AI and Data Science Research Center) at the Global Research Institute of Technology and Engineering, North Carolina, United States. He has more than 28 years of teaching and research experience in information technology (Software Development, Database Technology, AI Engineering, Data Engineering, Data Science, Data Analytics, IoT-based Technologies, and Cloud Computing) at the Universities of Science and Technology in Vietnam, India, and USA. He has been the chair session for 20 conferences, keynote speaker for more than 25 international conclaves; an expert tech speaker for 100 over seminars and webinars; an international technical board member for 10 international organizations; an editorial board member for more than 5 ISSNs; an international reviewer and evaluator for more than 100 journal papers; an international examiner and evaluator for more than 15 PhD. theses in computer science field. He has been contributing to various research activities in fields of AI and data science while publishing many international articles in renowned journals and conference proceedings. He has published 52 authored books (in computer science between 2000-2010), 2 authored books (software development), 10 book chapters, 4 edited books, and 9 edited books (calling for book chapters) in the fields of AI ecosystem (AI, ML, DL, robotics, data science, big data, and IoT), smart city ecosystem, healthcare ecosystem, fintech technology, and blockchain technology (since 2020). He has over 28 years of nonstop work as a software product manager, data engineer, AI engineer, cloud computing architect, solution architect, software architect, database expert in the foreign corporations of Germany, Sweden, the United States, Singapore, and multinationals (former CEO,