TORNADO-Omics Techniques and Neural Networks for the Development of Predictive Risk Models
Integration of Omics-based Technologies and Artificial Intelligence to Identify Predictive Risk Models in a Air Force's Pilot Cohort for the Maintenance of Safety, Well-being, Health, and Performance to be Translated to Civil Population
Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico
200 participants
Feb 5, 2024
OBSERVATIONAL
Conditions
Summary
The goal of this observational study is to define a personalized risk model in the super healthy and homogeneous population of Italian Air Force high-performance pilots. This peculiar cohort conducts dynamic activities in an extreme environment, compared to a population of military people not involved in flight activity. The study integrates the analyses of biological samples (urine, blood, and saliva), clinical records, and occupational data collected at different time points and analyzed by omic-based approaches supported by Artificial Intelligence. Data resulting from the study will clarify many etiopathological mechanisms of diseases, allowing the creation of a model of analyses that can be extended to the civilian population and patient cohorts for the potentiation of precision and preventive medicine.
Eligibility
Plain Language Summary
Simplified for easier understanding
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Interventions
Collection of biological samples (blood, urine, saliva) and clinical data
Locations(1)
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NCT06372054