# Artificial Intelligence for the Early Detection of Patients with Cognitive Impairment: A Scoping Review

## TL;DR

This review shows that AI tools can help detect early signs of cognitive impairment, which might be missed by healthcare professionals.

## Contribution

The study maps the impact of AI-based tools for early cognitive impairment detection and highlights their clinical and ethical implications.

## Key findings

- AI tools like deep-learning models show promising accuracy in detecting early cognitive changes.
- These tools identify subtle patterns difficult to detect with traditional assessments.
- Ethical concerns such as patient privacy and data security are raised by AI use.

## Abstract

What are the main findings?
Artificial Intelligence tools can contribute to the early detection of subtle cognitive changes, which may be challenging for healthcare professionals to identify.The review included 14 studies, mainly systematic reviews and diagnostic studies, supporting the clinical utility of Artificial Intelligence-based approaches.

Artificial Intelligence tools can contribute to the early detection of subtle cognitive changes, which may be challenging for healthcare professionals to identify.

The review included 14 studies, mainly systematic reviews and diagnostic studies, supporting the clinical utility of Artificial Intelligence-based approaches.

What are the implications of the main findings?
Artificial Intelligence-based tools could improve clinical decision-making and early intervention strategies in cognitive impairment.The use of Artificial Intelligence raises ethical considerations, particularly concerning patient privacy and data security.

Artificial Intelligence-based tools could improve clinical decision-making and early intervention strategies in cognitive impairment.

The use of Artificial Intelligence raises ethical considerations, particularly concerning patient privacy and data security.

Background/Objectives: Cognitive impairment affects multiple brain functions, and its early detection is essential to prevent progression to dementia; artificial intelligence has shown considerable potential in this field. This scoping review aims to map the impact of artificial intelligence–based tools for the early detection of cognitive impairment by identifying the main technologies used, examining their effectiveness, and exploring their ethical implications. Methods: A scoping review was conducted between April and May 2025 following the PRISMA-ScR methodological framework; the review protocol was previously registered on the Open Science Framework. PubMed, Scopus, and Cochrane databases were searched using natural language and controlled vocabulary terms via Medical Subject Headings. The search was limited to articles published between 2020 and 2025, in English or Spanish, with free full-text access. Methodological quality was assessed using CASPe, JBI, and MMAT. Results: A total of 14 studies were included after the selection and critical appraisal process. The findings show that artificial intelligence–based tools such as deep-learning models applied to neuroimaging, speech and gait analysis, electronic health record analysis, and mobile health applications demonstrate promising accuracy in detecting early cognitive changes. These technologies enable the identification of subtle patterns that may be difficult to detect using conventional clinical assessments. Conclusions: AI-based tools can provide substantial support for clinical decision-making by effectively identifying subtle changes that are imperceptible to human intelligence. However, their use also raises ethical issues related to patient privacy and data security.