Revealing the hidden knowledge in pathology big data: Machine learning to support clinical decision making for unknown infectious diseases and recognise biosecurity incursions in tropical Australia (Old ID 26978)
Role
Principal Investigator
Description
Pathology departments generate massive data from the results of routine and targeted tests conducted to serve community health needs. With the availability of large pathology data collections, the application of sophisticated machine learning (ML) algorithms allows the detection of novel data patterns to characterise disease processes and monitor population health. We will apply recursive partitioning (trees and forests) and support vector machines (SVM) to large pathology data sets to: (a) investigate the biosecurity potential of linked community data, and; (b) assist early decision support for patients presenting with a tropical pyrexia of unknown origin (PUOs).
Date
20 Aug 2020 - 30 Sep 2023
Project Type
GRANT
Keywords
Big data;Pathology;Biosecurity;Meloidosis;Arboviral disease;Machine learning
Funding Body
Tropical Australian Academic Health Centre Limited
Amount
48480
Project Team
Damon Eisen;Emma McBryde;Catherine Rush