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In parallel, the quality of adherence data analysis has increased due to guidelines on operational adherence definitions [15], advanced statistical analysis [16,17], and semiautomated procedures to analyze adherence in health care databases (eg, the Adhere-R package [18]).
JMIR Form Res 2024;8:e51013
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Studying R in an epidemiology course can help students develop important skills for data analysis, reproducibility, and collaboration, which are essential for conducting rigorous and impactful research in their field [2]. There are collections of functions that use R, known as R packages, which enhance the ability to conduct data analysis in diverse fields, such as medicine [3].
JMIR Med Educ 2023;9:e47394
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We developed an R package to run on parallel cores and automatically select by default the most efficient number of cores to use depending on the number of records to match, the number of available cores, and the available RAM. The number of cores used still fit in the parameters. We used the packages “future” and “future.apply” to enable Linux and Windows compatibility.
JMIR Med Inform 2022;10(11):e36711
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Leprosy Screening Based on Artificial Intelligence: Development of a Cross-Platform App
After initial processing with Python, the RF algorithm was applied to the resulting data using the R software package Random Forest. In addition to RF, there are several other machine-learning classification algorithms that could be appropriate for this task, such as naive Bayes [19], logistic regression [20], k-nearest neighbor [21], decision tree [22], and gradient boosting [23]. This list is not exhaustive, but includes the most common algorithms that were applied to our dataset for model comparison.
JMIR Mhealth Uhealth 2021;9(4):e23718
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