As the use of machine learning (ML) models in product development and data-driven
decision-making processes became pervasive in many domains, people's focus on building …

Research related to automatically detecting Alzheimer's disease (AD) is important, given the
high prevalence of AD and the high cost of traditional methods. Since AD significantly affects …

Introduction: Research related to the automatic detection of Alzheimer's disease (AD) is
important, given the high prevalence of AD and the high cost of traditional diagnostic …

Alzheimer's Disease (AD) is a form of dementia that affects the memory, cognition, and motor
skills of patients. Extensive research has been done to develop accessible, cost-effective …

Alzheimer's is a neurodegenerative disorder affecting the central nervous system and
cognitive processes, explicitly impairing detailed mental analysis. Throughout this condition …

Robust strategies for Alzheimer's disease (AD) detection are important, given the high
prevalence of AD. In this paper, we study the performance and generalizability of three …

Introduction: Alzheimer's disease is a type of dementia in which early diagnosis plays a
major rule in the quality of treatment. Among new works in the diagnosis of Alzheimer's …

Purpose This review was designed to provide a systematic overview of prosody in people
with a primary diagnosis of dementia (PwD) and evaluate the potential use of prosodic …

Understanding robustness and sensitivity of BERT models predicting Alzheimer's disease
from text is important for both developing better classification models and for understanding …

Background and objective Amyotrophic lateral sclerosis (ALS) frequently causes speech
impairments, which can be valuable early indicators of decline. Automated acoustic …