# Practical Statistical Considerations for the Clinical Validation of AI/ML-enabled Medical Diagnostic Devices

arXiv: https://arxiv.org/abs/2303.05399 · HTML: https://mlsanity.com/paper/2303.05399/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 51 references that are in the map.
- First posted on arXiv 2 Mar 2023.

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

- [Is there a role for statistics in artificial intelligence?](https://mlsanity.com/paper/2009.09070/) (2020)

## Built on by (most cited first, 1 of 1)

- [Rapid Review of Generative AI in Smart Medical Applications](https://mlsanity.com/paper/2406.06627/) (2024)

## Abstract (arXiv)

Artificial Intelligence (AI) and Machine-Learning (ML) models have been increasingly used in medical products, such as medical device software. General considerations on the statistical aspects for the evaluation of AI/ML-enabled medical diagnostic devices are discussed in this paper. We also provide relevant academic references and note good practices in addressing various statistical challenges in the clinical validation of AI/ML-enabled medical devices in the context of their intended use.