Liam Scanlon

Liam Scanlon

I'm a medical researcher and developer eager to contribute to the field.

Featured Research

Machine Learning Integration of Clinical and Echocardiographic Data Predicts Long-Term Survival Following Myocardial Infarction

This research demonstrates how machine learning models, specifically XGBoost, integrating clinical and comprehensive echocardiographic data are superior to traditional methods for predicting long-term all-cause mortality after myocardial infarction.

Complete Revascularization in STEMI Patients with Multivessel Disease: A Meta-analysis of Contemorary Randomised Trials

This meta-analysis of sixteen randomised controlled trials including 15,160 patients found that complete revascularisation at the time of STEMI presentation with multivessel disease was associated with a lower risk of death or MI compared culprit only revascularisation.

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Other Projects

Road Network Visualiser

Interactive visualization of Australia's road network.

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Train Simulation Game

A casual train simulation game experience.

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Horde Holdout

A strategic defense game against incoming hordes.

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Let's Connect

I'm open to collaborating on research or projects. Feel free to reach out!