WHO ICTRP trial
Evaluating the ability of machine learning to predict hospital admissions from…
ACTRN12624000615583 · Australian New Zealand Clinical Trials Registry (ANZCTR) · Recruiting
Key facts
| Trial ID | ACTRN12624000615583 |
|---|---|
| Public title | Evaluating the ability of machine learning to predict hospital admissions from emergency department triage at St John of God Midland Hospital using data from 2016 to 2023. |
| Scientific title | Evaluating the performance of machine learning in predicting hospital admissions from emergency department triage, addressing concept drift and incremental learning at SJOG Midland Hospital using 2016 to 2023 data. |
| Primary sponsor | Dr Ethan Williams |
| Secondary sponsors | University of Notre Dame, Australia |
| Registry | Australian New Zealand Clinical Trials Registry (ANZCTR) |
| Recruitment status | Recruiting |
| Study type | Interventional |
| Phase | Not Applicable |
| Countries | Australia |
| Conditions | Health service research; Health service research;Emergency medicine - Other emergency care;Public Health - Health service research |
| Interventions | A machine learning model (both a neural network (NN) and a extreme gradient boosting (XGB) machine) will be trained on the first year of data of all presentations to the SJOG Midland Emergency Department (2016). It will then use this data… |
| Registration date | Oct 5, 2024 |
| Target size | 550000 |
| Registry page | anzctr.org.au |
At a glance
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About WHO ICTRP trial registrations
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Source: World Health Organization (WHO), International Clinical Trials Registry Platform (ICTRP) · Source date: