Implementation of three methods based on the diversity forest (DF) algorithm 
  (Hornung, 2022, <doi:10.1007/s42979-021-00920-1>), a split-finding approach that 
  enables complex split procedures in random forests.
  The package includes:
    1. Interaction forests (IFs) (Hornung & Boulesteix, 2022, <doi:10.1016/j.csda.2022.107460>): 
    Model quantitative and qualitative interaction effects using bivariable splitting. 
    Come with the Effect Importance Measure (EIM), which can be used to identify variable 
    pairs that have well-interpretable quantitative and qualitative interaction effects 
    with high predictive relevance.
	2. Two random forest-based variable importance measures (VIMs) for multi-class outcomes: 
	the class-focused VIM, which ranks covariates by their ability to distinguish individual 
	outcome classes from the others, and the discriminatory VIM, which measures overall 
	covariate influence irrespective of class-specific relevance.
    3. The basic form of diversity forests that uses conventional univariable, binary 
    splitting (Hornung, 2022).
  Except for the multi-class VIMs, all methods support categorical, metric, and survival 
  outcomes. The package includes visualization tools for interpreting the identified 
  covariate effects.
  Built as a fork of the 'ranger' R package (main author: Marvin N. Wright), which 
  implements random forests using an efficient C++ implementation.

Provides tools to sort DICOM-format medical image files, and
    convert them to NIfTI-1 format.

Curated datasets and intuitive data management functions to streamline epidemiological data workflows. It is designed to support researchers in quickly accessing clean, structured data and applying essential cleaning, summarizing, visualization, and export operations with minimal effort. Whether you're preparing a cohort for analysis or creating reports, 'DIVINE' makes the process more efficient, transparent, and reproducible.

A set of tools for empirical analysis of diversity (a number 
    and frequency of different types in a population) and similarity 
    (a number and frequency of shared types in two populations) in 
    biological or ecological systems.