Methods for Enhancing the Reproducibility of Observational Research Using Electronic Health Records: Preliminary Findings from the CALIBER Resource. - Spiros C. Denaxas; Arturo Gonzalez-Izquierdo; Maria Pikoula; Kenan Direk; Natalie K. Fitzpatrick; Harry Hemingway; Liam Smeeth (CBMS, 2017)

Evaluation of Machine Learning Methods to Predict Coronary Artery Disease Using Metabolomic Data. - Henrietta Forssen; Riyaz S. Patel; Natalie K. Fitzpatrick; Aroon D. Hingorani; Adam Timmis; Harry Hemingway; Spiros C. Denaxas (CoRR, 2017)

Phenotyping UK Electronic Health Records from 15 Million Individuals for Precision Medicine: The CALIBER Resource. - Spiros C. Denaxas; Arturo Gonzalez-Izquierdo; Natalie K. Fitzpatrick; Kenan Direk; Harry Hemingway (ICIMTH, 2019)

Analysing the Heterogeneity of Rule-Based EHR Phenotyping Algorithms in CALIBER and the UK Biobank. - Spiros C. Denaxas; Helen Parkinson; Natalie K. Fitzpatrick; Cathie Sudlow; Harry Hemingway (KDH@IJCAI, 2019)

UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. - Spiros C. Denaxas; Arturo Gonzalez-Izquierdo; Kenan Direk; Natalie K. Fitzpatrick; Ghazaleh Fatemifar; Amitava Banerjee; Richard J. B. Dobson; Laurence J. Howe; Valerie Kuan; R. Tom Lumbers; Laura Pasea; Riyaz S. Patel; et al. (J. Am. Medical Informatics Assoc., 2019)

A survey on clinical natural language processing in the United Kingdom from 2007 to 2022. - Honghan Wu; Minhong Wang 002; Jinge Wu; Farah Francis; Yun-Hsuan Chang; Alex Shavick; Hang Dong 002; Michael Tin Chung Poon; Natalie K. Fitzpatrick; Adam P. Levine; Luke T. Slater; Alex Handy; et al. (npj Digit. Medicine, 2022)