# ConGaIT: A Clinician-Centered Dashboard for Contestable AI in Parkinson's Disease Care

arXiv: https://arxiv.org/abs/2507.22300 · HTML: https://mlsanity.com/paper/2507.22300/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jul 2025.

## Built on by (most cited first, 3 of 3)

- [Motion2Meaning: A Clinician-Centered Framework for Contestable LLM in Parkinson's Disease Gait Interpretation](https://mlsanity.com/paper/2512.08934/) (2025)
- [SimInterview: Transforming Business Education through Large Language Model-Based Simulated Multilingual Interview Training System](https://mlsanity.com/paper/2508.11873/) (2025)
- [OGA-AID: Clinician-in-the-loop AI Report Drafting Assistant for Multimodal Observational Gait Analysis in Post-Stroke Rehabilitation](https://mlsanity.com/paper/2604.05360/) (2026)

## Abstract (arXiv)

AI-assisted gait analysis holds promise for improving Parkinson's Disease (PD) care, but current clinical dashboards lack transparency and offer no meaningful way for clinicians to interrogate or contest AI decisions. We present Con-GaIT (Contestable Gait Interpretation & Tracking), a clinician-centered system that advances Contestable AI through a tightly integrated interface designed for interpretability, oversight, and procedural recourse. Grounded in HCI principles, ConGaIT enables structured disagreement via a novel Contest & Justify interaction pattern, supported by visual explanations, role-based feedback, and traceable justification logs. Evaluated using the Contestability Assessment Score (CAS), the framework achieves a score of 0.970, demonstrating that contestability can be operationalized through human-centered design in compliance with emerging regulatory standards. A demonstration of the framework is available at https://github.com/hungdothanh/Con-GaIT.