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McGill AI Platform Flags Respiratory Infections Days Before Symptoms

Validated in The Lancet Digital Health with near-90% accuracy, the platform now moves to real-world testing for clinical integration.

Overview

  • The system continuously monitors data from a smart ring, watch and smart T-shirt to detect acute systemic inflammation, an early marker of respiratory infections.
  • In a controlled trial of 55 volunteers given a live attenuated flu vaccine, the selected AI model achieved nearly 90% sensitivity in predicting infection before symptoms emerged.
  • Algorithms also flagged immune responses in four incidental COVID-19 cases up to 72 hours before symptom onset or PCR confirmation.
  • By combining heart rate, variability, body temperature, respiratory rate and blood pressure readings, the AI captures subtle physiological shifts that individual measures miss.
  • Researchers are now refining the data-efficient model for clinical use to alert patients and clinicians to pre-symptomatic inflammation and support preventive care pathways.