Showing 1 - 5 results of 5 for search '"emergency department"', query time: 0.06s Refine Results
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    Student-teacher curriculum learning via reinforcement learning: predicting hospital inpatient admission location by el-Bouri, R, Eyre, D, Watkinson, P, Zhu, T, Clifton, DA

    Published 2020
    “…Accurate and reliable prediction of hospital admission location is important due to resource-constraints and space availability in a clinical setting, particularly when dealing with patients who come from the emergency department. In this work we propose a student-teacher network via reinforcement learning to deal with this specific problem. …”
    Conference item
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    ScoEHR: generating synthetic electronic health records using continuous-time diffusion models by Naseer, AA, Walker, B, Landon, C, Ambrosy, A, Fudim, M, Wysham, N, Toro, B, Swaminathan, S, Lyons, T

    Published 2023
    “…ScoEHR is shown to outperform three baseline synthetic EHR generation frameworks (medGAN, medWGAN, and medBGAN) on two publicly available datasets, MIMIC-III and the Yale New Haven Health System Emergency Department dataset, based on four widely accepted metrics of data utility. …”
    Conference item
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    Pack size restriction of mild analgesics sold as over-the-counter drugs in pharmacies in Denmark: preliminary register findings by Morthorst, B, Erlangsen, A, Hawton, K, Dalhoff, K, Nordentoft, M

    Published 2017
    “…Mild analgesics are sold in all European countries, and some countries have observed increased contact with emergency departments due to overdose by these agents, especially paracetamol. …”
    Conference item
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    27 The DiPEP (Diagnosis of PE in Pregnancy) study: can clinical assessment, d-dimer or chest x-ray be used to select pregnant or postpartum women with suspected PE for diagnostic i... by Goodacre, S, Horspool, K, Nelson-Piercy, C, Knight, M, Shephard, N, Lecky, F, Thomas, S, Hunt, B, Fuller, G

    Published 2017
    “…To determine whether clinical features (in the form of a clinical decision rule) or d-dimer can be used to select pregnant or postpartum women with suspected PE for diagnostic imaging.Observational cohort study augmented with additional cases.Consultant-led maternity units participating in the UK Obstetric Surveillance System (UKOSS) and emergency departments and maternity units at eleven prospectively recruiting sites.198 pregnant or postpartum women with diagnosed PE identified through UKOSS and 324 pregnant or postpartum women with suspected PE from prospectively recruiting sites.Data were collected relating to clinical features, elements of clinical decision rules, d-dimer measurements, diagnostic imaging, treatment for PE and adverse outcomes.Women were classified as having or not having PE on the basis of diagnostic imaging, treatment and subsequent adverse outcomes. …”
    Conference item