Deep learning for Alzheimer's disease diagnosis: A survey

M Khojaste-Sarakhsi, SS Haghighi… - Artificial intelligence in …, 2022 - Elsevier
Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …

A multi-modal feature embedding approach to diagnose alzheimer disease from spoken language

S Zargarbashi, B Babaali - arXiv preprint arXiv:1910.00330, 2019 - arxiv.org
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 …

Lexical features are more vulnerable, syntactic features have more predictive power

J Novikova, A Balagopalan, K Shkaruta… - Proceedings of the 5th …, 2019 - aclanthology.org
Understanding the vulnerability of linguistic features extracted from noisy text is important for
both developing better health text classification models and for interpreting vulnerabilities of …

[PDF][PDF] A long short-term memory deep learning network for MRI based Alzheimer's disease dementia classification

SM Gnanasegar, B Bhasuran… - J Appl Bioinforma …, 2020 - researchgate.net
MRI data has been widely used for early detection and diagnosis of Alzheimer's disease.
This work outlines a deep learning based Long Short-Term Memory (LSTM) algorithm …

Design, Determination, and Evaluation of Gender-Based Bias Mitigation Techniques for Music Recommender Systems

S Shrestha - 2023 - search.proquest.com
The majority of smartphone users engage with a recommender system on a daily basis.
Many rely on these recommendations to make their next purchase, download the next game …

Predictor neutralization in predictive data analysis systems

P Ford, B Ironside - US Patent 11,954,603, 2024 - Google Patents
There is a need for more effective and efficient predictive data analysis. Various
embodiments of the present invention address one or more of the noted technical …