Intelligent risk prediction in public health using wearable device data.
NPJ Digit Med
; 5(1): 153, 2022 Oct 13.
Article
in English
| MEDLINE | ID: covidwho-2062278
ABSTRACT
The importance of infection risk prediction as a key public health measure has only been underscored by the COVID-19 pandemic. In a recent study, researchers use machine learning to develop an algorithm that predicts the risk of COVID-19 infection, by combining biometric data from wearable devices like Fitbit, with electronic symptom surveys. In doing so, they aim to increase the efficiency of test allocation when tracking disease spread in resource-limited settings. But the implications of technology that applies data from wearables stretch far beyond infection monitoring into healthcare delivery and research. The adoption and implementation of this type of technology will depend on regulation, impact on patient outcomes, and cost savings.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Observational study
/
Prognostic study
Language:
English
Journal:
NPJ Digit Med
Year:
2022
Document Type:
Article
Affiliation country:
S41746-022-00701-x
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