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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
de Almeida, A., M.Breternitz & napoli, O. O. (2022). An intelligent systems approach for early illness symptoms detection: AIM (your) Health .   1a Conferência de Saúde Societal.
Exportar Referência (IEEE) 
A. M. Almeida et al.,  "An intelligent systems approach for early illness symptoms detection: AIM (your) Health ", in   1a Conferência de Saúde Societal, 2022
Exportar BibTeX 
@null{almeida2022_1715081934689,
	year = "2022",
	url = "https://iscte-saude.iscte-iul.pt"
}
Exportar RIS 
TY  - GEN
TI  - An intelligent systems approach for early illness symptoms detection: AIM (your) Health 
T2  -   1a Conferência de Saúde Societal
AU  - de Almeida, A.
AU  - M.Breternitz
AU  - napoli, O. O.
PY  - 2022
UR  - https://iscte-saude.iscte-iul.pt
AB  - We aim to develop a conceptual model for a smart system that uses data collected by personal mobile devices for the early detection of disease and subsequent issuing of an alert. Using data obtained from mobile devices, preferably smartphones or smartwatches, such as the heart rate, the number of daily steps, cough or breathing sounds, and blood oxygenation level, it is possible to build a “diary” of biometric signals, usable in the most diverse situations. Notably, it is possible to build a status configuration that characterises the user of that device and monitors his/her general status. This configuration, once obtained, can then be used by a model specially trained for anomaly detection that can issue an alert of a change in state with possible medical significance. This alert can be emitted only to the user or, with permission, to flag a health platform and the professional who usually follows the user.
 

ER  -