Artificial intelligence for cognitive health assessment: state-of-the-art, open challenges and future directions

AR Javed, A Saadia, H Mughal, TR Gadekallu… - Cognitive …, 2023 - Springer
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 …

[HTML][HTML] Subgrouping and structural brain connectivity of Parkinson's disease–past studies and future directions

T Samantaray, J Saini, CN Gupta - Neuroscience Informatics, 2022 - Elsevier
Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder associated with
several motor and non-motor dysfunctions. The wide variety of clinical features often leads to …

Graph embedded ensemble deep randomized network for diagnosis of alzheimer's disease

AK Malik, M Tanveer - IEEE/ACM Transactions on …, 2022 - ieeexplore.ieee.org
Randomized shallow/deep neural networks with closed form solution avoid the
shortcomings that exist in the back propagation (BP) based trained neural networks …

[Retracted] Homogeneous Decision Community Extraction Based on End‐User Mental Behavior on Social Media

S Gupta, S Kumar, SL Bangare… - Computational …, 2022 - Wiley Online Library
Aiming at the inadequacy of the group decision‐making method with the current attribute
value as interval language information, an interval binary semantic decision‐making method …

Analisis Sentimen Pada Ulasan Aplikasi Amazon Shopping Di Google Play Store Menggunakan Naive Bayes Classifier

E Hasibuan, EA Heriyanto - Jurnal Teknik dan Science, 2022 - journal.admi.or.id
Sentiment analysis or opinion mining is a study that analyzes people's opinions, thoughts
and impressions on various topics, subjects, and products or services. The development of …

Spatially informed Bayesian neural network for neurodegenerative diseases classification

D Payares‐Garcia, J Mateu, W Schick - Statistics in medicine, 2023 - Wiley Online Library
Magnetic resonance imaging (MRI) plays an increasingly important role in the diagnosis and
prognosis of neurodegenerative diseases. One field of extensive clinical use of MRI is the …

Machine Learning‐Based Multimodel Computing for Medical Imaging for Classification and Detection of Alzheimer Disease

FH Alghamedy, M Shafiq, L Liu, A Yasin… - Computational …, 2022 - Wiley Online Library
Alzheimer is a disease that causes the brain to deteriorate over time. It starts off mild, but
over the course of time, it becomes increasingly more severe. Alzheimer's disease causes …

Artificial intelligence for dementia research methods optimization

M Bucholc, C James, AA Khleifat… - Alzheimer's & …, 2023 - Wiley Online Library
Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being
used in dementia research. However, several methodological challenges exist that may limit …

Machine Learning-Assisted Near-Infrared Spectral Fingerprinting for Macrophage Phenotyping

A Nadeem, S Lyons, A Kindopp, A Jamieson… - ACS …, 2024 - ACS Publications
Spectral fingerprinting has emerged as a powerful tool that is adept at identifying chemical
compounds and deciphering complex interactions within cells and engineered …

Alzheimer's disease diagnosis from MRI and SWI fused image using self adaptive differential evolutionary RVFL classifier

T Goel, S Verma, M Tanveer, PN Suganthan - Information Fusion, 2025 - Elsevier
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that involves gradual
memory loss and eventually leads to severe cognitive decline at the final stage. Advanced …