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epicR - Evaluation Platform in Chronic Obstructive Pulmonary Disease

Evaluation Platform in Chronic Obstructive Pulmonary Disease (EPIC) is a Discrete Event Simulation (DES) model that simulates health outcomes of patients with Chronic Obstructive Pulmonary Disease (COPD) based on demographics and individual-level risk factors, based on the model published in Sadatsafavi et al. (2019) <doi:10.1177/0272989X18824098>.

Last updated

openblascpp

8.02 score 13 stars 45 scripts 526 downloads

predtools - Prediction Model Tools

Provides additional functions for evaluating predictive models, including plotting calibration curves and model-based Receiver Operating Characteristic (mROC) based on Sadatsafavi et al (2021) <arXiv:2003.00316>.

Last updated

cpp

7.61 score 11 stars 1 dependents 155 scripts 501 downloads

accept - The Acute COPD Exacerbation Prediction Tool (ACCEPT)

Allows clinicians to predict the rate and severity of future acute exacerbation in Chronic Obstructive Pulmonary Disease (COPD) patients, based on the clinical prediction models published in Adibi et al. (2020) <doi:10.1016/S2213-2600(19)30397-2> and Safari et al. (2022) <doi:10.1016/j.eclinm.2022.101574>.

Last updated

5.33 score 10 stars 17 scripts 250 downloads

cumulcalib - Cumulative Calibration Assessment for Prediction Models

Tools for visualization of, and inference on, the calibration of prediction models on the cumulative domain. This provides a method for evaluating calibration of risk prediction models without having to group the data or use tuning parameters (e.g., loess bandwidth). This package implements the methodology described in Sadatsafavi and Patkau (2024) <doi:10.1002/sim.10138>. The core of the package is cumulcalib(), which takes in vectors of binary responses and predicted risks. The plot() and summary() methods are implemented for the results returned by cumulcalib().

Last updated

4.00 score 2 stars 9 scripts 617 downloads