# Sample size determination for machine learning in medical research

arXiv: https://arxiv.org/abs/2503.05809 · HTML: https://mlsanity.com/paper/2503.05809/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 10 references that are in the map.
- First posted on arXiv 4 Mar 2025.

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

- [How many images do I need? Understanding how sample size per class affects deep learning model performance metrics for balanced designs in autonomous wildlife monitoring](https://mlsanity.com/paper/2010.08186/) (2020)

## Abstract (arXiv)

Machine learning (ML) methods are being increasingly used across various domains of medicine research. However, despite advancements in the use of ML in medicine, clear and definitive guidelines for determining sample sizes in medical ML research are lacking. This article proposes a method for determining sample sizes for medical research utilizing ML methods, beginning with the determination of the testing set sample size, followed with the determination of the training set and total sample sizes.