Researchers from the UK recently developed a real-time machine learning framework that uses dynamic patient contact networks to predict hospital-onset COVID-19 infections at the patient level. This information came to us from News-Medical in their article, “Machine learning predicts hospital-onset COVID-19 infections using patient contact networks.”
Accurate and real-time disease prediction is vital for the prevention and control of healthcare-related infections. Although contacts between individuals are primarily responsible for infection chains, most prediction frameworks do not capture the contact dynamics.
This was the first study to predict individual patient hospital-onset COVID-19 infections using routine patient and hospital data and dynamic contact networks.
Using emerging technologies like machine learning to directly impact patient care and outcomes is a positive trend. Technology continues to play more of a role in health care. This is all part of the drive to bring collaboration and efficiency to healthcare records.
Melody K. Smith
Sponsored by Access Innovations, changing search to found.
