H. Hemingway

First name
H.
Last name
Hemingway
Banerjee, A., Dashtban, A., Chen, S., Pasea, L., Thygesen, J. H., Fatemifar, G., et al. (2023). Identifying subtypes of heart failure from three electronic health record sources with machine learning: an external, prognostic, and genetic validation study. Lancet Digit Health, 5, e370-e379. http://doi.org/10.1016/s2589-7500(23)00065-1
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Jordan, K. P., Rathod-Mistry, T., van der Windt, D. A., Bailey, J., Chen, Y., Clarson, L., et al. (2023). Determining cardiovascular risk in patients with unattributed chest pain in UK primary care: an electronic health record study. Eur J Prev Cardiol. http://doi.org/10.1093/eurjpc/zwad055
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Dashtban, A., Mizani, M. A., Pasea, L., Denaxas, S., Corbett, R., Mamza, J. B., et al. (2023). Identifying subtypes of chronic kidney disease with machine learning: development, internal validation and prognostic validation using linked electronic health records in 350,067 individuals. Ebiomedicine, 89, 104489. http://doi.org/10.1016/j.ebiom.2023.104489
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Mizani, M. A., Dashtban, A., Pasea, L., Lai, A. G., Thygesen, J., Tomlinson, C., et al. (2022). Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19-a data-driven retrospective cohort study. J R Soc Med, 1410768221131897. http://doi.org/10.1177/01410768221131897
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Kuan, V., Denaxas, S., Patalay, P., Nitsch, D., Mathur, R., Gonzalez-Izquierdo, A., et al. (2022). Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study. Lancet Digit Health. http://doi.org/10.1016/s2589-7500(22)00187-x
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Rapsomaniki, E., Shah, A., Perel, P., Denaxas, S., George, J., Nicholas, O., et al. (2014). Prognostic models for stable coronary artery disease based on electronic health record cohort of 102 023 patients. Eur Heart J, 35, 844-52. http://doi.org/10.1093/eurheartj/eht533
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Dashtban, A., Mizani, M. A., Denaxas, S., Nitsch, D., Quint, J., Corbett, R., et al. (2022). A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease. Kidney Int. http://doi.org/10.1016/j.kint.2022.05.015
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Jordan, K. P., Rathod-Mistry, T., Bailey, J., Chen, Y., Clarson, L., Denaxas, S., et al. (2022). Long-Term Cardiovascular Risk and Management of Patients Recorded in Primary Care With Unattributed Chest Pain: An Electronic Health Record Study. J Am Heart Assoc, 11, e023146. http://doi.org/10.1161/jaha.121.023146
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Martin, R. M., Hemingway, H., Gunnell, D., Karsch, K. R., Baumbach, A., & Frankel, S. (2002). Population need for coronary revascularisation: are national targets for England credible?. Heart.
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Shah, A. D., Nicholas, O., Timmis, A. D., Feder, G., Abrams, K. R., Chen, R., et al. (2011). Threshold haemoglobin levels and the prognosis of stable coronary disease: two new cohorts and a systematic review and meta-analysis. PLoS Med. http://doi.org/10.1371/journal.pmed.1000439
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