Clinical prediction models

Clinical prediction models

Clinical prediction models (also known as prognostic models, risk scores) are mathematical equations that relate multiple predictors (risk factors, co-variates) to the probability of having a disease or condition (diagnostic) or the probability that an event will happen in the future (prognostic).

Bibliografske podrobnosti
Main Authors:	Ranstam, J, Cook, J, Collins, G
Format:	Journal article
Jezik:	English
Izdano:	Wiley 2016

Podobne knjige/članki

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Statistical models and confounding adjustment
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Statistical analyses that provide an effect size are to be preferred
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Kaplan-Meier curve
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Number needed to treat
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The rise of big clinical databases.
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Time to restrict the use of p-values in Acta Orthopaedica
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Improved glycemic control with no weight increase in patients with type 2 diabetes after once-daily treatment with the long-acting glucagon-like peptide 1 analog liraglutide (NN2211): a 12-week, double-blind, randomized, controlled trial.
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Stability of clinical prediction models developed using statistical or machine learning methods
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Cardiovascular disease risk prediction in the UK: Which is the best risk prediction model?
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Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems?
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Statistical concerns in the development of a prediction model
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Comparing risk prediction models.
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Statistical flaws in the development of a prediction model.
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A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
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