A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence

Iuliu Alexandru Pap () and Stefan Oniga
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Iuliu Alexandru Pap: Department of Electric, Electronic and Computer Engineering, Technical University of Cluj-Napoca, North University Center of Baia Mare, 430083 Baia Mare, Romania
Stefan Oniga: Department of Electric, Electronic and Computer Engineering, Technical University of Cluj-Napoca, North University Center of Baia Mare, 430083 Baia Mare, Romania

IJERPH, 2022, vol. 19, issue 18, 1-15

Abstract: Over the last couple of years, in the context of the COVID-19 pandemic, many healthcare issues have been exacerbated, highlighting the paramount need to provide both reliable and affordable health services to remote locations by using the latest technologies such as video conferencing, data management, the secure transfer of patient information, and efficient data analysis tools such as machine learning algorithms. In the constant struggle to offer healthcare to everyone, many modern technologies find applicability in eHealth, mHealth, telehealth or telemedicine. Through this paper, we attempt to render an overview of what different technologies are used in certain healthcare applications, ranging from remote patient monitoring in the field of cardio-oncology to analyzing EEG signals through machine learning for the prediction of seizures, focusing on the role of artificial intelligence in eHealth.

Keywords: eHealth; mHealth; telehealth; telemedicine; remote patient monitoring; Internet of Things; brain–computer interface; artificial intelligence; machine learning; deep learning (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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