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Analysis of Existing Severity Scores and Development of New Models for Hospital Mortality Prediction
Başlık:
Analysis of Existing Severity Scores and Development of New Models for Hospital Mortality Prediction
Yazar:
Baden, Lucy Marie, author.
ISBN:
9780438079786
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (74 pages)
Genel Not:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Frederic R. Paik Schoenberg Committee members: Yingnian Wu; Hongquan Xu.
Özet:
Severity scoring systems are frequently used in hospital intensive care units to assess patient wellness and mortality probability. Accurate mortality predictions are vital to provide appropriate and timely treatments to critical patients. However, commonly used severity scores have been found to make inaccurate mortality predictions. In this paper, we assess and compare four popular severity scores for both discrimination and calibration. We apply logistic regression, random forest, and neural network classification techniques in order to present new mortality prediction models, and compare their performance with pre-existing scores. We also compare the use of a basic set of predictor features that can be easily collected in the ICU environment with an expanded predictor set including laboratory diagnostics. Newly developed models improved on existing severity scores in terms of discrimination, with random forest providing the best results, but often demonstrated poor calibration. The expanded variable set did not improve model performance.
Notlar:
School code: 0031
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Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(695064.1) | 695064-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
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