# CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models

arXiv: https://arxiv.org/abs/2307.08673 · HTML: https://mlsanity.com/paper/2307.08673/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 14 references that are in the map.
- First posted on arXiv 17 Jul 2023.

## Builds on (most cited first, 1 of 1)

- [MRQy: An Open-Source Tool for Quality Control of MR Imaging Data](https://mlsanity.com/paper/2004.04871/) (2020)

## Abstract (arXiv)

Batch effects (BEs) refer to systematic technical differences in data collection unrelated to biological variations whose noise is shown to negatively impact machine learning (ML) model generalizability. Here we release CohortFinder, an open-source tool aimed at mitigating BEs via data-driven cohort partitioning. We demonstrate CohortFinder improves ML model performance in downstream medical image processing tasks. CohortFinder is freely available for download at cohortfinder.com.