Area of research
Statistics and Probability · Toxicology
Research interest
Research interests include Pharmacovigilance and Adverse Drug Reactions, Advanced Causal Inference Techniques, Biomedical Text Mining and Ontologies, and Machine Learning in Healthcare.
Semaglutide and Nonarteritic Anterior Ischemic Optic Neuropathy
Risk of Thyroid Tumors With GLP-1 Receptor Agonists: A Retrospective Cohort Study
Advancing Real-World Evidence Through a Federated Health Data Network (EHDEN): Descriptive Study
Semaglutide and diabetic retinopathy: an OHDSI network study
Comparative Effectiveness of Second-Line Antihyperglycemic Agents for Cardiovascular Outcomes
Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research
Abstract 4118762: Large-scale multinational trends in the use of cardioprotective antihyperglycemic agents as first-line therapy in patients with type 2 diabetes and cardiovascular disease: a LEGEND-T2DM study
European Health Data & Evidence Network—learnings from building out a standardized international health data network
Multinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM
Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort study
Large-scale evidence generation and evaluation across a network of databases for type 2 diabetes mellitus (LEGEND-T2DM): a protocol for a series of multinational, real-world comparative cardiovascular effectiveness and safety studies
DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models
Comparative First-Line Effectiveness and Safety of ACE (Angiotensin-Converting Enzyme) Inhibitors and Angiotensin Receptor Blockers: A Multinational Cohort Study
A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data
Comprehensive Comparative Effectiveness and Safety of First-Line β-Blocker Monotherapy in Hypertensive Patients
Association of Ticagrelor vs Clopidogrel With Net Adverse Clinical Events in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention
Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study
Comparison of Cardiovascular and Safety Outcomes of Chlorthalidone vs Hydrochlorothiazide to Treat Hypertension
Renin–angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis
Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study
Learning from local to global: An efficient distributed algorithm for modeling time-to-event data
Comprehensive comparative effectiveness and safety of first-line antihypertensive drug classes: a systematic, multinational, large-scale analysis
Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm
Evaluating large-scale propensity score performance through real-world and synthetic data experiments
Empirical confidence interval calibration for population-level effect estimation studies in observational healthcare data
Prenatal antidepressant use and risk of attention-deficit/hyperactivity disorder in offspring: population based cohort study
Prenatal antidepressant exposure and the risk of attention-deficit hyperactivity disorder in children: A systematic review and meta-analysis
Characterizing treatment pathways at scale using the OHDSI network
Robust empirical calibration of <i>p</i>‐values using observational data
Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers