Dr Richard A Armstrong
PhD Fellow | Anaesthetist | Clinician Data Scientist
I am an anaesthetist in the Severn Deanery and a GW4-CAT PhD Programme for Health Professionals PhD Fellow studying the use of multiomics in predicting and understanding immune-mediated complications of anaesthesia and surgery. My research interests focus on applying machine learning and causal inference to improve patient outcomes after major surgery.
Research Pillars
Multiomics & Biobank Data
Analyzing large-scale genetic and multiomic datasets to identify molecular pathways and predict surgical complications.
Clinical Machine Learning
Developing robust adaptive predictive pipelines to identify patients at risk of postoperative complications.
Causal Inference
Applying causal machine learning methods to discover targetable drivers of clinical outcomes.
Selected Publications
All Publications (Google Scholar) →The genetic architecture of postoperative delirium after major surgery and its relationship with nonpostoperative neurocognitive conditions: A genome-wide association study
Large-scale UK Biobank analysis of >140,000 individuals uncovering genetic risk factors for postoperative delirium and its relationship to Alzheimer's Disease risk.
Using multiomic data to predict postoperative complications after major surgery in the UK Biobank cohort
Developed adaptive machine learning predictive pipelines utilizing clinical and multiomic (metabolomics, proteomics) features to forecast postoperative complication risk.
Outcomes from intensive care in patients with COVID-19: a systematic review and meta-analysis
A landmark meta-analysis showing COVID-19 ICU mortality over time. Over 500 citations to date and informed national and international clinical guidelines.