Search alternatives:
significant codes » significant models (Expand Search), significant genes (Expand Search), significant degs (Expand Search)
greater decrease » greater increase (Expand Search), greater increases (Expand Search), rate decreased (Expand Search)
codes increased » cases increased (Expand Search), costs increased (Expand Search), confers increased (Expand Search)
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search), we decrease (Expand Search)
significant codes » significant models (Expand Search), significant genes (Expand Search), significant degs (Expand Search)
greater decrease » greater increase (Expand Search), greater increases (Expand Search), rate decreased (Expand Search)
codes increased » cases increased (Expand Search), costs increased (Expand Search), confers increased (Expand Search)
step decrease » sizes decrease (Expand Search), teer decrease (Expand Search), we decrease (Expand Search)
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Usage of clinical code types other than official Read V2 codes by year in the WLGP RRDA.
Published 2025Subjects: -
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Summary of clinical code types added to the WLGP RRDA look-up (excluding official Read V2 codes).
Published 2025Subjects: -
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ICD-10-GM codes for the identification of SSI and designated NRZ classification.
Published 2022Subjects: -
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Thematic structure and coding description.
Published 2025“…<div><p>Childhood obesity levels continue to rise, with significant impact on individuals and the NHS. The ‘Complications of Excess Weight’ (CEW) clinics provide support to young people with complications of their weight. …”
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Pseudo code for coupling model execution process.
Published 2024“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
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