Towards Early Detection of Mild Cognitive Impairment: Predictive Analytics Using the Oculo-Cognitive Addition Test (OCAT)

Gaurav N. Pradhan, Gaurav N. Pradhan, Sarah E. Kingsbury, Michael J. Cevette, Jan Stepanek, Richard J. Caselli

2025

Abstract

Mild cognitive impairment (MCI) is often challenging to diagnose. The Oculo-Cognitive Addition Test (OCAT) is a rapid, objective tool that measures eye movement and time-based features during mental addition tasks in under one minute. This study aims to develop predictive machine learning algorithms for early detection of those at greater risk for mild cognitive impairment, helping warrant further testing. OCAT testing with integrated eye tracking was completed by 250 patients. Time-related and eye movement features were extracted from raw gaze data. Feature selection was performed using machine learning methods, including random forest and univariate decision trees, to identify predictors of Dementia Rating Scale (DRS) outcomes. Supervised models-logistic regression (LR) and K-nearest neighbors (KNN)-were trained to classify MCI. Class imbalance was addressed using the Synthetic Minority Over-sampling Technique. LR models achieved the highest performance using the combined time and eye movement features, with an accuracy of 0.97, recall of 0.91, and the area under the precision-recall curve (AUPRC) of 0.95. This study demonstrates that machine learning models trained on OCAT-derived features can reliably predict DRS outcomes (PASS/FAIL), offering a promising approach for early identification of MCI.

Paper Citation

in Harvard Style

Pradhan G., Kingsbury S., Cevette M., Stepanek J. and Caselli R. (2025). Towards Early Detection of Mild Cognitive Impairment: Predictive Analytics Using the Oculo-Cognitive Addition Test (OCAT). In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN , SciTePress, pages 457-464. DOI: 10.5220/0013808300004000

in Bibtex Style

@conference{kdir25,
author={Gaurav Pradhan and Sarah Kingsbury and Michael Cevette and Jan Stepanek and Richard Caselli},
title={Towards Early Detection of Mild Cognitive Impairment: Predictive Analytics Using the Oculo-Cognitive Addition Test (OCAT)},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2025},
pages={457-464},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013808300004000},
isbn={},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - Towards Early Detection of Mild Cognitive Impairment: Predictive Analytics Using the Oculo-Cognitive Addition Test (OCAT)
SN -
AU - Pradhan G.
AU - Kingsbury S.
AU - Cevette M.
AU - Stepanek J.
AU - Caselli R.
PY - 2025
SP - 457
EP - 464
DO - 10.5220/0013808300004000
PB - SciTePress