Y. Li

First name
Y.
Last name
Li
Tianyi, F. L., Li, Y., Alderdice, F., Quigley, M. A., Kurinczuk, J. J., Bankhead, C., & Carson, C. (2022). The association between conception history and subsequent postpartum depression and/or anxiety: Evidence from the Clinical Practice Research Datalink 1991-2013. J Affect Disord, 310, 266-273. http://doi.org/10.1016/j.jad.2022.04.138
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Van Staa, T., Li, Y., Gold, N., Chadborn, T., Welfare, W., Palin, V., et al. (2022). Comparing antibiotic prescribing between clinicians in UK primary care: an analysis in a cohort study of eight different measures of antibiotic prescribing. Bmj Qual Saf. http://doi.org/10.1136/bmjqs-2020-012108
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Li, Y., Molter, A., White, A., Welfare, W., Palin, V., Belmonte, M., et al. (2019). Relationship between prescribing of antibiotics and other medicines in primary care: a cross-sectional study. Br J Gen Pract. http://doi.org/10.3399/bjgp18X700457
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Li, Y., Sperrin, M., Belmonte, M., Pate, A., Ashcroft, D. M., & van Staa, T. P. (2019). Do population-level risk prediction models that use routinely collected health data reliably predict individual risks?. Sci Rep. http://doi.org/10.1038/s41598-019-47712-5
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van Staa, T. P., Palin, V., Li, Y., Welfare, W., Felton, T. W., Dark, P., & Ashcroft, D. M. (2020). The effectiveness of frequent antibiotic use in reducing the risk of infection-related hospital admissions: results from two large population-based cohorts. BMC Med. http://doi.org/10.1186/s12916-020-1504-5
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Li, Y., Sperrin, M., Martin, G. P., Ashcroft, D. M., & van Staa, T. P. (2020). Examining the impact of data quality and completeness of electronic health records on predictions of patients\textquoteright risks of cardiovascular disease. Int J Med Inform. http://doi.org/10.1016/j.ijmedinf.2019.104033
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Li, Y., Rao, S., Solares, J. R. A., Hassaine, A., Ramakrishnan, R., Canoy, D., et al. (2020). BEHRT: Transformer for Electronic Health Records. Sci Rep. http://doi.org/10.1038/s41598-020-62922-y
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Li, Y., Sperrin, M., Ashcroft, D. M., & van Staa, T. P. (2020). Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar. Bmj. http://doi.org/10.1136/bmj.m3919
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Mistry, C., Palin, V., Li, Y., Martin, G. P., Jenkins, D., Welfare, W., et al. (2020). Development and validation of a multivariable prediction model for infection-related complications in patients with common infections in UK primary care and the extent of risk-based prescribing of antibiotics. BMC Med. http://doi.org/10.1186/s12916-020-01581-2
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Li, Y., Kurinczuk, J. J., Gale, C., Siassakos, D., & Carson, C. (2021). Evidence of disparities in the provision of the maternal postpartum 6-week check in primary care in England, 2015-2018: an observational study using the Clinical Practice Research Datalink (CPRD). J Epidemiol Community Health. http://doi.org/10.1136/jech-2021-216640
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