Trends of Artificial Intelligence and Big Data for E-Health
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Beschreibung
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.
This book aims to present evidence of the crucial importance of artificial intelligence and big data for medical decision making and data analysis in different fields of E-Health such as radiology, cancer prevention, drugs discovery, COVID-19 detection, AI and blockchain, cardiac imaging, cybersecurity, etc. Big data analytics and artificial intelligence have the potential to lead the methodology of healthcare providers using sophisticated technologies for accurate analysis of clinical data repositories and assist in making informed decisions, while ensuring confidentiality and data security. The challenges of intelligent Health depend basically on the opportunities provided by the community of experts to make health systems more sustainable. In intelligent healthcare, Big Data is based on massive data collected routinely or automatically, and stored electronically. The re-usability of this data could include links between existing databases to improve theperformance and efficiency of the health system.Big data and artificial intelligence data will produce significant and accurate results to support medical decision making. The process would benefit from patient's data and their clinical history to support the experts in providing a more personalized medical overview. The intelligent health approach has the potential to allow a close surveillance of the patient's progress during therapy.
Artificial intelligence (AI) and Big data are more than a digital transformation trend in healthcare Digital Transformation in healthcare will reshape diagnosis, disease prevention, and personalization of health services Privacy of medical data and the associated cybersecurity risks will be the main challenges in implementing digital healthcare strategies
Autor*in
Houneida Sakly
Themen in »Trends of Artificial Intelligence and Big Data for E-Health«
Digital Health Predictive and Personalised Medicine Artificial Intelligence Deep Learning Machine Learning Big Data Assisted-software Data analysis Cybersecurity in Healthcare Medical Augmented Reality Healthcare Business Technology Data Science