Skip to main content

Published

Re-engineering a machine learning phenotype to adapt to the changing COVID-19 landscape: a machine learning modelling study from the N3C and RECOVER consortia.
Crosskey M. The Lancet Digital Health 2025;:https://doi.org/10.1016/j.landig.2025.100887.
[By eschewing the COVID-19 index date as an anchor point for analysis, we can assess the probability of long COVID among patients who might have tested at home, or with suspected (but untested) cases of COVID-19, or multiple SARS-CoV-2 reinfections. We view this exercise as a model for maintaining and updating any machine learning pipeline used for clinical research and operations.]
Freely available online

Age Groups
Adults
Conditions and Lifestyle Factors
Coronavirus Infections
Professional Interests
Robotics and Artificial Intelligence
Settings
Community Clinics
General Practice
Staff Groups
Clinical Scientist
Public Health Specialist