Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/30416
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dc.contributor.authorPires, Ivan Miguelen_US
dc.contributor.authorDobre, Ciprianen_US
dc.contributor.authorZdravevski, Eftimen_US
dc.contributor.authorGarcia, Nuno Men_US
dc.date.accessioned2024-06-05T12:40:57Z-
dc.date.available2024-06-05T12:40:57Z-
dc.date.issued2023-09-20-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/30416-
dc.description.abstractThe 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.en_US
dc.publisherFrontiersen_US
dc.relation.ispartofFrontiers in Digital Healthen_US
dc.titleWearable and mobile data analysis methodologies for personalized medicineen_US
dc.typeJournal Articleen_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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