Anoop D. Shah

Natural Language Processing for Mimicking Clinical Trial Recruitment in Critical Care: A Semi-Automated Simulation Based on the LeoPARDS Trial

Hegler Tissot, Richard J. B. Dobson, Amos Folarin, 2019, IEEE Journal of Biomedical and Health Informatics.

Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease

Nicholas M. Luscombe, Harry Hemingway, Anoop D. Shah, 2018 .

CALIBERrfimpute: Imputation in MICE using Random Forest

Harry Hemingway, Anoop D. Shah, Jonathan W. Bartlett, 2014 .

An informatics consult approach for generating clinical evidence for treatment decisions

Spiros Denaxas, Richard J. B. Dobson, Harry Hemingway, 2021, BMC Medical Informatics and Decision Making.

Threshold Haemoglobin Levels and the Prognosis of Stable Coronary Disease: Two New Cohorts and a Systematic Review and Meta-Analysis

Keith R. Abrams, Gene Feder, Harry Hemingway, 2011, PLoS medicine.

Prognostic burden of heart failure recorded in primary care, acute hospital admissions, or both: a population‐based linked electronic health record cohort study in 2.1 million people

Spiros Denaxas, Harry Hemingway, Anoop D. Shah, 2016, European journal of heart failure.

Extracting Diagnoses and Investigation Results from Unstructured Text in Electronic Health Records by Semi-Supervised Machine Learning

John Shawe-Taylor, Spiros Denaxas, Zhuoran Wang, 2012, PloS one.

Defining Disease Phenotypes Using National Linked Electronic Health Records: A Case Study of Atrial Fibrillation

Katherine I. Morley, Harry Hemingway, Spiros C. Denaxas, 2014, PloS one.