R. Lumbers

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Elkheder, M., Gonzalez-Izquierdo, A., Arfeen, Q. U., Kuan, V., Lumbers, R. T., Denaxas, S., & Shah, A. D. (2022). Translating and evaluating historic phenotyping algorithms using SNOMED CT. J Am Med Inform Assoc. http://doi.org/10.1093/jamia/ocac158
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
Papez, V., Moinat, M., Payralbe, S., Asselbergs, F. W., Lumbers, R. T., Hemingway, H., et al. (2021). Transforming and evaluating electronic health record disease phenotyping algorithms using the OMOP common data model: a case study in heart failure. JAMIA Open. http://doi.org/10.1093/jamiaopen/ooab001
Katsoulis, M., Lai, A. G., Diaz-Ordaz, K., Gomes, M., Pasea, L., Banerjee, A., et al. (2021). Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records. Lancet Diabetes Endocrinol. http://doi.org/10.1016/s2213-8587(21)00207-2
Kuan, V., Fraser, H. C., Hingorani, M., Denaxas, S., Gonzalez-Izquierdo, A., Direk, K., et al. (2021). Data-driven identification of ageing-related diseases from electronic health records. Sci Rep. http://doi.org/10.1038/s41598-021-82459-y