Abstract Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully
provided automated solutions to numerous real-world problems. Healthcare is one of the …

The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led
many researchers to explore ways to automate the process to make it more objective and to …

Objective We develop a deep learning framework based on the pre-trained Bidirectional
Encoder Representations from Transformers (BERT) model using unstructured clinical notes …

Background Electronic health records (EHRs) contain patients' health information over time,
including possible early indicators of disease. However, the increasing amount of data …

Dementia is an incurable neurodegenerative disease primarily affecting the older
population, for which the World Health Organisation has set to promoting early diagnosis …

Objective: Intrinsic capacity is recognized as an important determinant of healthy aging and
well-being of older adults; however, relatively little is known about the intrinsic capacity of …

Abstract Aims and Objectives The objective of this scoping review is to explore the types and
mechanisms of Artificial intelligence (AI) techniques for detecting mild cognitive impairment …

Background: The growing number of older adults in recent decades has led to more
prevalent geriatric diseases, such as strokes and dementia. Therefore, Alzheimer's disease …

Over 78 million people will suffer from dementia by 2030, emphasizing the need for early
identification of patients with mild cognitive impairment (MCI) at risk, and personalized …

This study assesses the ability of state-of-the-art large language models (LLMs) including
GPT-3.5, GPT-4, Falcon, and LLaMA 2 to identify patients with mild cognitive impairment …