An overview of causal machine learning methodology in Electronic Health Records

Dr Maurice O’Connell gave a talk on current work with Dr Matthew Sperrin and the DynAIRx team in the area of statistics and causal inference and causal machine learning. Maurice talked about causal inference methodology development applied to electronic health records in the areas of deprescribing or continuing\initiating medications in individuals and populations with polypharmacy and multimorbidity and selecting individuals with polypharmacy and multimorbidity for structured medication reviews. This session was organised by the AI for Multiple Long Term Conditions Research Support Facility (link to the same archived website). AIM RSF is funded by the NIHR Artificial Intelligence for Multiple Long-Term Conditions (AIM) programme (NIHR202647).

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-19
DOI
https://doi.org/10.5281/zenodo.15050554
Primary Topic
Advanced Causal Inference Techniques
Type
article
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article

An overview of causal machine learning methodology in Electronic Health Records

Zenodo (CERN European Organization for Nuclear Research)
Advanced Causal Inference Techniques
article

An overview of causal machine learning methodology in Electronic Health Records

article en

Abstract

Dr Maurice O’Connell gave a talk on current work with Dr Matthew Sperrin and the DynAIRx team in the area of statistics and causal inference and causal machine learning. Maurice talked about causal inference methodology development applied to electronic health records in the areas of deprescribing or continuing\initiating medications in individuals and populations with polypharmacy and multimorbidity and selecting individuals with polypharmacy and multimorbidity for structured medication reviews. This session was organised by the AI for Multiple Long Term Conditions Research Support Facility (link to the same archived website). AIM RSF is funded by the NIHR Artificial Intelligence for Multiple Long-Term Conditions (AIM) programme (NIHR202647).

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 47%
Advanced Causal Inference Techniques
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