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Vicente Traver

Researcher at Polytechnic University of Valencia

Publications -  95
Citations -  1677

Vicente Traver is an academic researcher from Polytechnic University of Valencia. The author has contributed to research in topics: Process mining & Health care. The author has an hindex of 19, co-authored 89 publications receiving 1331 citations. Previous affiliations of Vicente Traver include Technical University of Madrid & Instituto Politécnico Nacional.

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Body area network for wireless patient monitoring

TL;DR: A BAN system is presented, which allows the connectivity of a wide range of heterogeneous body sensors to a portable hub device that is connectable to external networks (IEEE 802.11, GPRS) and can substantially improve the performance of different services, especially those that are health related.
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Are Health Videos from Hospitals, Health Organizations, and Active Users Available to Health Consumers? An Analysis of Diabetes Health Video Ranking in YouTube.

TL;DR: The conclusions are that the current YouTube algorithm favors the presence of reliable videos in upper rank positions in diabetes-related searches and how videos from reliable channels, such as hospitals and health organizations, are evolving in the ranking is analyzed.
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Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems.

TL;DR: A tool and a process mining-based methodology that, using indoor location systems, enables health staff not only to represent the process, but to know precise information about the deployment of the process in an unobtrusive and transparent way is presented.
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Multimedia telehomecare system using standard TV set

TL;DR: A telehomecare multimedia platform that runs over integrated services digital network and internet protocol using videoconferencing standards H.320 and H.323, and a standard TV set for patient interaction that allows online remote monitoring: ECG, heart sound, blood pressure.
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Process mining for individualized behavior modeling using wireless tracking in nursing homes.

TL;DR: The eMotiva process mining algorithms are presented and suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection.