Emerging Trends in Early Dementia Diagnosis: An Analysis on Advanced Machine Learning Approaches

Dementia is the waning of cognitive abilities, which is typically seen with the natural aging process and includes issues with memory, language, and problem-solving abilities. Artificial Intelligence (AI) techniques are one viable method for the diagnosis of dementia. Despite recent advances in dementia informatics research and AI, accurate early diagnoses are still far from ideal. This study focuses on showcasing a comprehensive analysis of emerging AI approaches applied to early dementia diagnosis, highlighting trends across neuroimaging, speech, EEG, and clinical data. The proposed work’s main contributions include a summary of the potential challenges and vulnerabilities with dementia informatics research, a wide range of diagnostic issues in dementia care, a descriptive comparison of the elementary manuscripts judged on evaluation parameters such as precision, responsiveness, and definiteness and an offering of a descriptive set of data for developing Machine Learning (ML) and Deep Learning (DL) models. The manuscript also provides a valuable overview of new avenues for informatics research on dementia and advanced ML. The main objective is to fill a gap in the literature by offering an in-depth analysis and overview of the application of AI in dementia research, providing a foundational roadmap for accelerating impactful, data-driven dementia care solutions.