Trends of artificial intelligence and big data for e-health / Houneida Sakly, Kristen Yeom, Safwan Halabi, Mourad Said, Jayne Seekins, Moncef Tagina, editors.
Sakly, Houneida. editor.; Yeom, Kristen. editor.; Halabi, Safwan. editor.; Said, Mourad. editor.; Seekins, Jayne. editor.; Tagina, Moncef. editor.
2022
R859.7.A78 T74 2022
Available Online

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Title Trends of artificial intelligence and big data for e-health / Houneida Sakly, Kristen Yeom, Safwan Halabi, Mourad Said, Jayne Seekins, Moncef Tagina, editors.
ISBN 9783031111990 (electronic bk.)
3031111990 (electronic bk.)
3031111982
9783031111983
DOI https://doi.org/10.1007/978-3-031-11199-0
Published Cham, Switzerland : Springer, [2022]
Language English
Description 1 online resource (1 volume) : illustrations (black and white, and colour)
Other Standard Identifiers 10.1007/978-3-031-11199-0 doi
Call Number R859.7.A78 T74 2022
Dewey Decimal Classification 610.285
Summary This book aims to present the impact of Artificial Intelligence (AI) and Big Data in healthcare for medical decision making and data analysis in myriad fields including Radiology, Radiomics, Radiogenomics, Oncology, Pharmacology, COVID-19 prognosis, Cardiac imaging, Neuroradiology, Psychiatry and others. This will include topics such as Artificial Intelligence of Thing (AIOT), Explainable Artificial Intelligence (XAI), Distributed learning, Blockchain of Internet of Things (BIOT), Cybersecurity, and Internet of (Medical) Things (IoTs). Healthcare providers will learn how to leverage Big Data analytics and AI as methodology for accurate analysis based on their clinical data repositories and clinical decision support. The capacity to recognize patterns and transform large amounts of data into usable information for precision medicine assists healthcare professionals in achieving these objectives. Intelligent Health has the potential to monitor patients at risk with underlying conditions and track their progress during therapy. Some of the greatest challenges in using these technologies are based on legal and ethical concerns of using medical data and adequately representing and servicing disparate patient populations. One major potential benefit of this technology is to make health systems more sustainable and standardized. Privacy and data security, establishing protocols, appropriate governance, and improving technologies will be among the crucial priorities for Digital Transformation in Healthcare.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Sakly, Houneida. editor.
Yeom, Kristen. editor.
Halabi, Safwan. editor.
Said, Mourad. editor.
Seekins, Jayne. editor.
Tagina, Moncef. editor.
Series Integrated science ; v. 9.
Available in Other Form TRENDS OF ARTIFICIAL INTELLIGENCE AND BIG DATA FOR E-HEALTH.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
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.

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