1 code implementation • 5 Sep 2023 • Adrian Wilkins-Caruana, Madhushi Bandara, Katarzyna Musial, Daniel Catchpoole, Paul J. Kennedy
This study aims to infer the actual treatment steps for a particular patient group from administrative health records (AHR) - a common form of tabular healthcare data - and address several technique- and methodology-based gaps in treatment pathway-inference research.
no code implementations • 27 Aug 2023 • Adrian Caruana, Madhushi Bandara, Katarzyna Musial, Daniel Catchpoole, Paul J. Kennedy
We identify and analyse which machine learning techniques are applied to AHRs and which health informatics applications are pursued in AHR-based research.
no code implementations • 12 Oct 2021 • Aakash Ahmad, Madhushi Bandara, Mahdi Fahmideh, Henderik A. Proper, Giancarlo Guizzardi, Jeffrey Soar
The outbreak of the SARS-CoV-2 pandemic of the new COVID-19 disease (COVID-19 for short) demands empowering existing medical, economic, and social emergency backend systems with data analytics capabilities.
no code implementations • 4 Oct 2021 • Adrian Caruana, Madhushi Bandara, Daniel Catchpoole, Paul J Kennedy
Electronic health records (EHR) reflect real-world treatment behaviours that are used to enhance healthcare management but present challenges; protocols and pathways are often loosely defined and with elements frequently not recorded in EHRs, complicating the enhancement.