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Mobile 5P-Medicine Approach for Cardiovascular Patients.
Pires, Ivan Miguel; Denysyuk, Hanna Vitaliyivna; Villasana, María Vanessa; Sá, Juliana; Lameski, Petre; Chorbev, Ivan; Zdravevski, Eftim; Trajkovik, Vladimir; Morgado, José Francisco; Garcia, Nuno M.
  • Pires IM; Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal.
  • Denysyuk HV; Escola de Ciências e Tecnologias, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal.
  • Villasana MV; Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal.
  • Sá J; Centro Hospitalar do Baixo Vouga, 3810-164 Aveiro, Portugal.
  • Lameski P; Faculty of Health Sciences, Universidade da Beira Interior, 6200-506 Covilhã, Portugal.
  • Chorbev I; Centro Hospitalar e Universitário do Porto, 4099-001 Oporto, Portugal.
  • Zdravevski E; Faculty of Computer Science and Engineering, SS. Cyril and Methodius University, 1000 Skopje, North Macedonia.
  • Trajkovik V; Faculty of Computer Science and Engineering, SS. Cyril and Methodius University, 1000 Skopje, North Macedonia.
  • Morgado JF; Faculty of Computer Science and Engineering, SS. Cyril and Methodius University, 1000 Skopje, North Macedonia.
  • Garcia NM; Faculty of Computer Science and Engineering, SS. Cyril and Methodius University, 1000 Skopje, North Macedonia.
Sensors (Basel) ; 21(21)2021 Oct 21.
Article en En | MEDLINE | ID: mdl-34770292
Medicine is heading towards personalized care based on individual situations and conditions. With smartphones and increasingly miniaturized wearable devices, the sensors available on these devices can perform long-term continuous monitoring of several user health-related parameters, making them a powerful tool for a new medicine approach for these patients. Our proposed system, described in this article, aims to develop innovative solutions based on artificial intelligence techniques to empower patients with cardiovascular disease. These solutions will realize a novel 5P (Predictive, Preventive, Participatory, Personalized, and Precision) medicine approach by providing patients with personalized plans for treatment and increasing their ability for self-monitoring. Such capabilities will be derived by learning algorithms from physiological data and behavioral information, collected using wearables and smart devices worn by patients with health conditions. Further, developing an innovative system of smart algorithms will also focus on providing monitoring techniques, predicting extreme events, generating alarms with varying health parameters, and offering opportunities to maintain active engagement of patients in the healthcare process by promoting the adoption of healthy behaviors and well-being outcomes. The multiple features of this future system will increase the quality of life for cardiovascular diseases patients and provide seamless contact with a healthcare professional.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Dispositivos Electrónicos Vestibles Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Dispositivos Electrónicos Vestibles Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article