Trends of Artificial Intelligence and Big Data for E-Health

1. AI and Big Data for Intelligent Health: Promise and Potential.- 2. AI and Big Data for Cancer Segmentation, Detection and Prevention.- 3. Radiology, AI and Big Data: Challenges and Opportunities for Medical Imaging.- 4. Neuroradiology: Current Status and Future Prospects.- 5. Big Data and AI in Cardiac Imaging.- 6. Artificial Intelligence and Big data for COVID-19 Diagnosis.- 7. AI and Big Data for Drug Discovery.- 8. Blockchain of IoMT (BIoMT): A New Paradigm for COVID-19 Pandemic: Application, Architecture, Technology, and Security.- 9. AI and Big Data for Therapeutic Strategies in Psychiatry.- 10. Distributed Learning in Healthcare.- 11. Cybersecurity in Healthcare.- 12. Radiology and Radiomics: Towards oncology Prediction with IA and Big Data.

Houneida Sakly is a PhD and Engineer in Medical Informatics. She is a member of the research program "deep learning analysis of Radiologic Imaging in Stanford university. Certified in Healthcare Innovation with MIT-Harvard Medical school. Her main field of research is the Data science (Artificial Intelligence, Big Data, blockchain, Internet of things...) applied in Healthcare.She is a member in the Integrated Science Association (ISA) in the Universal Scientific Education and Research Network (USERN) in Tunisia.Currently, she is serving as a lead editor for various book and special issue in the field of digital Transformation and data science in Healthcare.Recently, she has won the Best Researcher Award in the International Conference on Cardiology and Cardiovascular Medicine- San Francisco, United States.
Kristen Yeom is a Professor of Radiology at Stanford University with a research focus on clinical and translational studies of quantitative MRI. She is also on the executive board for Center for Artificial Intelligence in Medicine and Imaging at Stanford and serves as the Chair of the American Society of Pediatric Neuroradiology Grant Committee.    Her recent works include radiomic and machine-learning strategies for brain tumor evaluation, as well as various computer vision tasks in clinical imaging towards precision. Dr. Safwan Halabi is an Associate Professor of Radiology at the Northwestern University School of Medicine, Vice-Chair of Radiology Informatics, and Associate CMIO at Lurie Children's Hospital. He also serves as the Director of Fetal Imaging at The Chicago Institute for Fetal Health. He is board-certified in Radiology with a Certificate of Added Qualification in Pediatric Radiology. He is also board-certified in Clinical Informatics. He clinically practices fetal and pediatric imaging at Lurie Children's Hospital. Dr.Halabi's clinical and administrative leadership roles are directed at improving the quality of care,efficiency, and