*Electronic Health Records

Daniel, R. ., Jones, H. ., Gregory, J. W., Shetty, A. ., Francis, N. ., Paranjothy, S. ., & Townson, J. . (2024). Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm. Lancet Digit Health, 6, e386-e395. http://doi.org/10.1016/s2589-7500(24)00050-5
Nakao, Y. M., Nadarajah, R. ., Shuweihdi, F. ., Nakao, K. ., Fuat, A. ., Moore, J. ., … Gale, C. . (2024). Predicting incident heart failure from population-based nationwide electronic health records: protocol for a model development and validation study. BMJ Open, 14, e073455. http://doi.org/10.1136/bmjopen-2023-073455
Bolt, H. ., Suffel, A. ., Matthewman, J. ., Sandmann, F. ., Tomlinson, L. ., & Eggo, R. . (2023). Seasonality of acute kidney injury phenotypes in England: an unsupervised machine learning classification study of electronic health records. BMC Nephrol, 24, 234. http://doi.org/10.1186/s12882-023-03269-0
Joseph, R. M., Knaggs, R. D., Coupland, C. A. C., Taylor, A. ., Vinogradova, Y. ., Butler, D. ., … Jack, R. H. (2023). Frequency and impact of medication reviews for people aged 65 years or above in UK primary care: an observational study using electronic health records. BMC Geriatr, 23, 435. http://doi.org/10.1186/s12877-023-04143-2
Ford, E. ., Rooney, P. ., Hurley, P. ., Oliver, S. ., Bremner, S. ., & Cassell, J. . (2020). Can the Use of Bayesian Analysis Methods Correct for Incompleteness in Electronic Health Records Diagnosis Data? Development of a Novel Method Using Simulated and Real-Life Clinical Data. Front Public Health, 8, 54. http://doi.org/10.3389/fpubh.2020.00054
Meffen, A. ., Sayers, R. D., Gillies, C. L., Khunti, K. ., & Gray, L. J. (2022). Are major lower extremity amputations well recorded in primary care electronic health records?: Insights from primary care electronic health records in England. Prim Health Care Res Dev, 23, e77. http://doi.org/10.1017/s1463423622000718
Tyrer, F. ., Bhaskaran, K. ., & Rutherford, M. J. (2022). Immortal time bias for life-long conditions in retrospective observational studies using electronic health records. BMC Med Res Methodol, 22, 86. http://doi.org/10.1186/s12874-022-01581-1