Clinical Prediction Models
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Citations
Flexible Imputation of Missing Data
Risk prediction models: II. External validation, model updating, and impact assessment
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
External validation of a Cox prognostic model: principles and methods
Calibration: the Achilles heel of predictive analytics
References
Proposed research plan for the derivation of a new Cardiac Risk Index.
External Validation of a Multiparametric Magnetic Resonance Imaging–based Nomogram for the Prediction of Extracapsular Extension and Seminal Vesicle Invasion in Prostate Cancer Patients Undergoing Radical Prostatectomy
The original and simplified Wells rules and age-adjusted D-dimer testing to rule out pulmonary embolism: an individual patient data meta-analysis.
Supplementing the National Early Warning Score (NEWS2) for anticipating early deterioration among patients with COVID-19 infection
A predictive tool for an effective use of 18 F-FDG PET in assessing activity of sarcoidosis
Related Papers (5)
Frequently Asked Questions (7)
Q2. What is the purpose of a prediction model?
Clinical prediction models aim to predict an outcome of interest, for example, survival in high-grade glioma (HGG) patients or intraventricular hemorrhage in preterm infants, by combining two or more patient-related variables.
Q3. What are the main features of the prediction models?
The obtained predictions of these models can then be used for medical and shared decision-making such as initiating surgical treatment, and for example for guidance in planning future lifestyle.
Q4. What is the main point of the article?
As a result of overfitting, prediction models tend to have a too optimistic predictive performance in terms of discrimination and calibration [2].
Q5. What is the author's opinion on the article?
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
Q6. What is the important aspect of clinical prediction models?
with the rise of so many prediction models, the authors should be able to make firm conclusions which model to use on their patients.
Q7. What is the author's intent for the article?
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