Decoding cognitive health using machine learning: A comprehensive evaluation for diagnosis of significant memory concern

M Sajid, R Sharma, I Beheshti… - … : Data Mining and …, 2024 - Wiley Online Library
The timely identification of significant memory concern (SMC) is crucial for proactive
cognitive health management, especially in an aging population. Detecting SMC early …

Granular ball twin support vector machine with pinball loss function

A Quadir, M Tanveer - IEEE Transactions on Computational …, 2024 - ieeexplore.ieee.org
Alzheimer's disease (AD) and Schizophrenia (SCZ) are prominent neurodegenerative
conditions and leading causes of dementia, resulting in progressive cognitive decline and …

Advancements in Alzheimer's disease classification using deep learning frameworks for multimodal neuroimaging: A comprehensive review

P Upadhyay, P Tomar, SP Yadav - Computers and Electrical Engineering, 2024 - Elsevier
Over the past years, Alzheimer's disease has emerged as a serious concern for people's
health. Researchers are facing challenges in effectively categorizing and diagnosing the …

Deep evidential fusion with uncertainty quantification and reliability learning for multimodal medical image segmentation

L Huang, S Ruan, P Decazes, T Denœux - Information Fusion, 2025 - Elsevier
Single-modality medical images generally do not contain enough information to reach an
accurate and reliable diagnosis. For this reason, physicians commonly rely on multimodal …

GB-RVFL: Fusion of randomized neural network and granular ball computing

M Sajid, A Quadir, M Tanveer… - Pattern Recognition, 2024 - Elsevier
The random vector functional link (RVFL) network is a prominent classification model with
strong generalization ability. However, RVFL treats all samples uniformly, ignoring whether …

Multiview random vector functional link network for predicting DNA-binding proteins

A Quadir, M Sajid, M Tanveer - arXiv preprint arXiv:2409.02588, 2024 - arxiv.org
The identification of DNA-binding proteins (DBPs) is a critical task due to their significant
impact on various biological activities. Understanding the mechanisms underlying protein …

Soft sensing modeling of penicillin fermentation process based on local selection ensemble learning

F Huang, L Li, C Du, S Wang, X Liu - Scientific Reports, 2024 - nature.com
In the process of penicillin fermentation, there is a strong nonlinear relationship between the
input eigenvector and multiple output vectors, which makes the prediction accuracy of the …

Brain Age Estimation Using Universum Learning-Based Kernel Random Vector Functional Link Regression Network

R Pilli, T Goel, R Murugan, M Tanveer - Cognitive Computation, 2024 - Springer
Brain age serves as a vital biomarker for detecting neurological ailments like Alzheimer's
disease (AD) and Parkinson's disease (PD). Magnetic resonance imaging (MRI) has been …

An Ensemble of InceptionNet and MobileNet Pretrained Deep Learning Models for Classifying Stages of Dementia

M Pandiyarajan, RS Valarmathi, GM Eda… - 2024 15th …, 2024 - ieeexplore.ieee.org
Dementia is a growing brain disorder, with Alzheimer's disease accounting for 60-70% of
cases. By 2050, nearly 10 million people may be affected. To help early detection, we …

Bridging the Gap: Integrating Machine Learning With Biomarkers for Enhanced Alzheimer's Detection and Tracking

R Ravi, TP Sridevi, NN Devi… - Deep Generative Models …, 2025 - igi-global.com
Alzheimer's Disease (AD) is a relentless neurodegenerative disorder that profoundly affects
cognitive abilities. Early detection and precise tracking of AD progression are pivotal for …