Trends of Artificial Intelligence and Big Data for E-Health (電子健康中的人工智慧與大數據趨勢)

本書旨在呈現人工智慧和大數據在醫療決策及各種電子健康（E-Health）領域（如放射學、癌症預防、藥物發現、COVID-19 檢測、人工智慧與區塊鏈、心臟影像學、網路安全等）中的關鍵重要性。大數據分析和人工智慧有潛力引領醫療提供者使用先進技術對臨床數據庫進行準確分析，並協助做出明智的決策，同時確保機密性和數據安全。智能健康的挑戰基本上取決於專家社群提供的機會，以使健康系統更具可持續性。在智能醫療中，大數據基於常規或自動收集的大量數據，並以電子方式儲存。這些數據的重用可能包括現有數據庫之間的連結，以改善健康系統的性能和效率。大數據和人工智慧數據將產生顯著且準確的結果，以支持醫療決策。該過程將受益於患者的數據及其臨床歷史，以協助專家提供更個性化的醫療概覽。智能健康方法有潛力在治療過程中對患者的進展進行密切監測。

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 patient safety. He has also led strategic efforts to improve the enterprise imaging platforms at Lurie Children's Hospital. He is a strong advocate of patient-centric care and has helped guide policies for radiology reports and image release to patients. He has published in peer-reviewed journals on various clinical and informatics topics. His current academic and research interests include imaging informatics, deep/machine learning in imaging, artificial intelligence in medicine, clinical decision support, and patient-centric health care delivery. He is currently the Chair of the RSNA Informatics Data Science Committee and serves as a Board Member for the Society for Imaging Informatics in Medicine.
Mourad Said, MD. Associate Professor in radiology and medical imaging since 2002. Member of the regional committee Africa-Middle East of the Radiological Society of North America RSNA 2014-2018. Author Reviewer for the prestigious Journal "Radiology" for many years. Different scientific presentations in RSNA meetings. He is board-certified in MRI from South Paris university. Qualifications in Pediatric/ Obstetric Radiology and MSK Imaging. He is actually interested in artificial intelligence in medical Imaging, deep learning and Radiomics with different publications. Jayne Seekins. Clinical Assistant Professor of Radiology, Stanford University. Research interests include fellow, resident and medical student education as well as Global Health.
Moncef TAGINA. Professor of Higher education and the co-founder of the COSMOS Laboratory in the National School of Computer Sciences (ENSI) in Tunisia (ENSI).He is the Director of the Doctoral School and President of the thesis committee .

Houneida Sakly 是一位醫療資訊學的博士及工程師。她是史丹佛大學「放射影像深度學習分析」研究計畫的成員。她擁有麻省理工學院-哈佛醫學院的醫療創新認證。她的主要研究領域是應用於醫療保健的數據科學（人工智慧、大數據、區塊鏈、物聯網等）。她是突尼西亞全球科學教育與研究網絡（USERN）整合科學協會（ISA）的成員。目前，她擔任數位轉型及醫療數據科學領域各種書籍和特刊的主編。最近，她在美國舊金山舉行的國際心臟病學與心血管醫學會議中獲得最佳研究者獎。

Kristen Yeom 是史丹佛大學的放射學教授，研究重點在於定量MRI的臨床及轉譯研究。她也是史丹佛醫學與影像人工智慧中心的執行委員會成員，並擔任美國兒童神經放射學會贈款委員會的主席。她最近的研究包括用於腦腫瘤評估的放射組學和機器學習策略，以及在臨床影像中針對精準醫療的各種計算機視覺任務。

Dr. Safwan Halabi 是西北大學醫學院的放射學副教授，放射學資訊副主席，以及Lurie兒童醫院的副首席醫療資訊官。他還擔任芝加哥胎兒健康研究所的胎兒影像主任。他在放射學領域獲得董事會認證，並擁有兒童放射學的附加資格證書。他在Lurie兒童醫院臨床實踐胎兒及兒童影像學。Halabi博士的臨床及行政領導角色旨在改善護理質量、效率和病人安全。他還主導了改善Lurie兒童醫院企業影像平台的戰略努力。他是病人中心護理的堅定倡導者，並協助指導放射學報告及影像釋放給病人的政策。他在各種臨床及資訊學主題上發表過同行評審的期刊文章。他目前的學術及研究興趣包括影像資訊學、影像中的深度/機器學習、醫學中的人工智慧、臨床決策支持及病人中心的醫療服務。他目前是RSNA資訊數據科學委員會的主席，並擔任醫學影像資訊學會的董事會成員。

Mourad Said, MD，自2002年以來擔任放射學及醫療影像的副教授。曾任北美放射學會（RSNA）非洲-中東地區委員會成員（2014-2018）。多年來擔任著名期刊《Radiology》的作者審稿人。在RSNA會議上進行過不同的科學報告。他在南巴黎大學獲得MRI的董事會認證，並具備兒童/婦產放射學及肌肉骨骼影像的資格。他目前對醫療影像中的人工智慧、深度學習及放射組學感興趣，並有多篇相關出版物。

Jayne Seekins 是史丹佛大學的臨床助理教授，研究興趣包括研究員、住院醫師及醫學生的教育，以及全球健康。

Moncef TAGINA 是高等教育教授，也是突尼西亞國立計算機科學學校（ENSI）COSMOS實驗室的共同創辦人。他是博士學校的主任及論文委員會的主席。