Machine Learning- AESI with COVID-19 vaccine
Clinical Prioritisation of COVID-19 Vaccine Adverse Events of Special Interest using Transformer-based Machine Learning Models
This initiative automatically categorises and ranks reports of adverse events following immunisation in Victorians. This supports the clinical team in prioritising the most urgent and important reports for rapid care, follow up and public health escalation if needed.
This is the product of informaticians working closely with clinicians to manage unprecedented volume of reports as the COVID-19 vaccines were rolled out across successfully the state. Initial results of this innovative approach are promising.
Chris Palmer leads the implementation of the machine learning model, and the team members are Sedigheh Khademi, Muhammad Javed, Jim Buttery, Gerardo Luis (Ikee) Dimaguila.
Congratulations to the team for winning the GSK Immunisation Award at the 2022 Communicable Diseases and Immunisation Conference.
Contacts
Gerardo Luis (Ikee) Dimaguila
Informatics Lead
Chris Palmer
Data Engineer