Ontology highlight
ABSTRACT: Background
Viral respiratory tract infections (VRTI) are extremely common. Considering the profound social and economic impact of COVID-19, it is imperative to identify novel mechanisms for early detection and prevention of VRTIs, to prevent future pandemics. Wearable biosensor technology may facilitate this. Early asymptomatic detection of VRTIs could reduce stress on the healthcare system by reducing transmission and decreasing the overall number of cases. The aim of the current study is to define a sensitive set of physiological and immunological signature patterns of VRTI through machine learning (ML) to analyze physiological data collected continuously using wearable vital signs sensors.Methods
A controlled, prospective longitudinal study with an induced low grade vira
SUBMITTER: Hadid A
PROVIDER: S-EPMC10049920 | biostudies-literature | 2023 May
REPOSITORIES: biostudies-literature