S. Denaxas

First name
S.
Last name
Denaxas
Denaxas, S., Gonzalez-Izquierdo, A., Direk, K., Fitzpatrick, N. K., Fatemifar, G., Banerjee, A., et al. (2019). UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. J Am Med Inform Assoc. http://doi.org/10.1093/jamia/ocz105
Uijl, A., Koudstaal, S., Direk, K., Denaxas, S., Groenwold, R. H. H., Banerjee, A., et al. (2019). Risk factors for incident heart failure in age- and sex-specific strata: a population-based cohort using linked electronic health records. Eur J Heart Fail. http://doi.org/10.1002/ejhf.1350
Williamson, E., Denaxas, S., Morris, S., Clarke, C. S., Thomas, M., Evans, H., et al. (2019). Risk of mortality and cardiovascular events following macrolide prescription in chronic rhinosinusitis patients: a cohort study using linked primary care electronic health records. Rhinology. http://doi.org/10.4193/Rhin18.237
Rafiq, M., Hayward, A., Warren-Gash, C., Denaxas, S., Gonzalez-Izquierdo, A., Lyratzopoulos, G., & Thomas, S. (2019). Socioeconomic deprivation and regional variation in Hodgkin\textquoterights lymphoma incidence in the UK: a population-based cohort study of 10 million individuals. BMJ Open. http://doi.org/10.1136/bmjopen-2019-029228
Banerjee, A., Allan, V., Denaxas, S., Shah, A., Kotecha, D., Lambiase, P. D., et al. (2019). Subtypes of atrial fibrillation with concomitant valvular heart disease derived from electronic health records: phenotypes, population prevalence, trends and prognosis. Europace. http://doi.org/10.1093/europace/euz220
Shah, A. D., Bailey, E., Williams, T., Denaxas, S., Dobson, R., & Hemingway, H. (2019). Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death. J Biomed Semantics. http://doi.org/10.1186/s13326-019-0214-4
Pikoula, M., Quint, J. K., Nissen, F., Hemingway, H., Smeeth, L., & Denaxas, S. (2019). Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records. BMC Med Inform Decis Mak. http://doi.org/10.1186/s12911-019-0805-0
Kuan, V., Denaxas, S., Izquierdo, G. -, Direk, K., Bhatti, O., Husain, S., et al. (2019). A chronological map of 308 physical and mental health conditions from 4 million individuals in the English National Health Service. The Lancet Digital Health. http://doi.org/10.1016/S2589-7500(19)30012-3
Hopkins, C., Williamson, E., Morris, S., Clarke, C. S., Thomas, M., Evans, H., et al. (2019). Antibiotic usage in chronic rhinosinusitis: analysis of national primary care electronic health records. Rhinology. http://doi.org/10.4193/Rhin19.136
Dickerman, B. A., Garcia-Albeniz, X., Logan, R. W., Denaxas, S., & Hernan, M. A. (2019). Avoidable flaws in observational analyses: an application to statins and cancer. Nat Med. http://doi.org/10.1038/s41591-019-0597-x