# AI-powered Language Assessment Tools for Dementia

arXiv: https://arxiv.org/abs/2209.12652 · HTML: https://mlsanity.com/paper/2209.12652/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 80 references that are in the map.
- First posted on arXiv 13 Sep 2022.

## Builds on (most cited first, 4 of 4)

- [Fairness in Machine Learning](https://mlsanity.com/paper/2012.15816/) (2020)
- [Detecting Linguistic Characteristics of Alzheimer's Dementia by Interpreting Neural Models](https://mlsanity.com/paper/1804.06440/) (2018)
- [On the importance of normative data in speech-based assessment](https://mlsanity.com/paper/1712.00069/) (2017)
- [Non-Pharmaceutical Intervention Discovery with Topic Modeling](https://mlsanity.com/paper/2009.13602/) (2020)

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

- [AI and Non AI Assessments for Dementia](https://mlsanity.com/paper/2307.01210/) (2023)

## Abstract (arXiv)

The main objective of this paper is to propose an approach for developing an Artificial Intelligence (AI)-powered Language Assessment (LA) tool. Such tools can be used to assess language impairments associated with dementia in older adults. The Machine Learning (ML) classifiers are the main parts of our proposed approach, therefore to develop an accurate tool with high sensitivity and specificity, we consider different binary classifiers and evaluate their performances. We also assess the reliability and validity of our approach by comparing the impact of different types of language tasks, features, and recording media on the performance of ML classifiers.