GPT model trained from scratch on EHR codes of 57 million individuals for universal risk prediction and trial emulation.
Representation learning for EHR data, exploring graph structures and semantic embeddings applied to national-scale datasets
Phenotyping at scale across diverse biobank cohorts to power genomic & proteomic analyses for target identification, drug discovery, and precision medicine.
Underpinned by the needs of patients, clinicians and researchers, the Disease Atlas is an ambitious project involving the generation of a systematic, data-driven knowledge across all common and rare diseases. Using newly available nationwide data on 56 million people the Atlas is generating novel comparative insights of the health needs of patients, the care provided, and the research that is carried out.
Deep-learning based analysis of sidestream dark field (SDF) imaging videos to quanitfy vascular perfusion in ICU patients.
Contributing clinical experience, data wrangling and analytical skills to development of COVID-19 Severity phenotypes from linked EHR data for 54 million patients in England.
Large expedition to Everest Base Camp seeking to characterise acclimatisation to environmental hypoxia in Sherpa's & Westerners to identify biomarkers of (mal-) adaptation that may inspire novel diagnostic/therapeutic targets for the cellular hypoxia seen in critical illness.
Established 'Innovation in Anaesthesia' BSc project leading to multidisciplinary and industrial collaboration