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Clinical Prediction Models
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TLDR
This paper presents a case study on survival analysis: Prediction of secondary cardiovascular events and lessons from case studies on overfitting and optimism in prediction models.Abstract:
Introduction.- Applications of prediction models.- Study design for prediction models.- Statistical models for prediction.- Overfitting and optimism in prediction models.- Choosing between alternative statistical models.- Dealing with missing values.- Case study on dealing with missing values.- Coding of categorical and continuous predictors.- Restrictions on candidate predictors.- Selection of main effects.- Assumptions in regression models: Additivity and linearity.- Modern estimation methods.- Estimation with external methods.- Evaluation of performance.- Clinical usefulness.- Validation of prediction models.- Presentation formats.- Patterns of external validity.- Updating for a new setting.- Updating for a multiple settings.- Prediction of a binary outcome: 30-day mortality after acute myocardial infarction.- Case study on survival analysis: Prediction of secondary cardiovascular events.- Lessons from case studies.read more
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Journal ArticleDOI
Postoperative neonatal mortality prediction using superlearning.
TL;DR: Superlearning provided improved or equivalent performance compared with individual regression and machine learning algorithms for predicting neonatal surgical mortality and should be considered for prediction in large data sets whenever complex mechanisms make parametric modeling assumptions unrealistic.
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Comparison of common machine learning models for classification of tuberculosis using transcriptional biomarkers from integrated datasets
TL;DR: A data analysis framework which directly integrates multiple publicly-available expression array datasets in order to identify a more reliable gene signature for the diagnosis of TB is proposed.
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Latin America validation of FACED score in patients with bronchiectasis: an analysis of six cohorts
Rodrigo Abensur Athanazio,Mônica Corso Pereira,Georgina Gramblicka,Fernando Cavalcanti-Lundgren,Mara Fernandes de Figueiredo,Francisco Arancibia,Samia Zahi Rached,David de la Rosa,Luis Máiz-Carro,Rosa Girón,Casilda Olveira,C. Prados,Miguel Ángel Martínez-García +12 more
TL;DR: The FACED score was confirmed as an excellent predictor of all-cause and respiratory mortality and severe exacerbations, as well as having excellent discriminative capacity for different degrees of severity in various bronchiectasis populations.
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A clinical prediction model to identify patients at high risk of death in the emergency department
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Developing a framework for evidence-based grading and assessment of predictive tools for clinical decision support.
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