Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/30416
Title: Wearable and mobile data analysis methodologies for personalized medicine
Authors: Pires, Ivan Miguel
Dobre, Ciprian
Zdravevski, Eftim 
Garcia, Nuno M
Issue Date: 20-Sep-2023
Publisher: Frontiers
Journal: Frontiers in Digital Health
Abstract: The Frontiers in Digital Health Research Topic Wearable and Mobile Data Analysis Methodologies for Personalized Medicine aimed to receive contributions related to the multidisciplinary field of personalized and precision medicine, which encompasses physics, statistics, telemedicine, biomedical engineering, digital signal processing, artificial intelligence, system engineering, and health privacy and security. Information and communication technologies have changed the landscape of many knowledge and societal areas, and medicine included. Bringing technology to the end users (or patients), a larger share of users can engage in personalized and precision therapies. Numerous and diverse pathologies can be monitored remotely, and as a consequence, better monitoring of health-related information may not only empower people but also hold the promise of aiding in the early detection of diseases.
URI: http://hdl.handle.net/20.500.12188/30416
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

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