Advancing healthcare through multimodal data fusion: a comprehensive review of techniques and applications

JR Teoh, J Dong, X Zuo, KW Lai, K Hasikin… - PeerJ Computer …, 2024 - peerj.com
With the increasing availability of diverse healthcare data sources, such as medical images
and electronic health records, there is a growing need to effectively integrate and fuse this …

[HTML][HTML] A review of deep learning-based information fusion techniques for multimodal medical image classification

Y Li, MEH Daho, PH Conze, R Zeghlache… - Computers in Biology …, 2024 - Elsevier
Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it
combines information from various imaging modalities to provide a more comprehensive …

Multi-scale multimodal deep learning framework for Alzheimer's disease diagnosis

M Abdelaziz, T Wang, W Anwaar, A Elazab - Computers in Biology and …, 2025 - Elsevier
Multimodal neuroimaging data, including magnetic resonance imaging (MRI) and positron
emission tomography (PET), provides complementary information about the brain that can …

Integrating artificial intelligence with smartphone-based imaging for cancer detection in vivo

B Song, R Liang - Biosensors and Bioelectronics, 2025 - Elsevier
Cancer is a major global health challenge, accounting for nearly one in six deaths
worldwide. Early diagnosis significantly improves survival rates and patient outcomes, yet in …

Patch-based interpretable deep learning framework for Alzheimer's disease diagnosis using multimodal data

H Zhang, M Ni, Y Yang, F **e, W Wang, Y He… - … Signal Processing and …, 2025 - Elsevier
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder and a major cause of
dementia worldwide. Accurate diagnosis of AD and its prodromal stage, mild cognitive …

XAI Unveiled: Revealing the Potential of Explainable AI in Medicine-A Systematic Review

N Scarpato, P Ferroni, F Guadagni - IEEE Access, 2024 - ieeexplore.ieee.org
Nowadays, artificial intelligence in medicine plays a leading role. This necessitates the need
to ensure that artificial intelligence systems are not only high-performing but also …

Multimodal multiview bilinear graph convolutional network for mild cognitive impairment diagnosis

G Wu, X Li, Y Xu, B Wei - Biomedical Physics & Engineering …, 2025 - iopscience.iop.org
Mild cognitive impairment (MCI) is a significant predictor of the early progression of
Alzheimer's disease (AD) and can serve as an important indicator of disease progression …

WIMOAD: Weighted Integration of Multi-Omics data for Alzheimer's Disease (AD) Diagnosis

H **ao, J Wang, S Wan - bioRxiv, 2024 - pmc.ncbi.nlm.nih.gov
As the most common subtype of dementia, Alzheimer's disease (AD) is characterized by a
progressive decline in cognitive functions, especially in memory, thinking, and reasoning …

A Multi-Scale Feature and Dual Self-Attention Mechanism for Enhanced Alzheimer's Disease Classification

J Wu, X Zhang, Y Li, Y Zhang, J Liu… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Magnetic resonance imaging (MRI) technology shows significant potential in predicting early
pathological changes associated with Alzheimer's disease (AD). However, the complexity of …

Neuro Vision AI for Reliable and Earlier Warning of Alzheimer's Disease

A Inbavalli, S Lakshmipriya… - 2024 International …, 2024 - ieeexplore.ieee.org
Alzheimer's disease is a very serious neurological condition. Memory loss and a progressive
decrease in mental capabilities are what ensue. This AD impacts millions of people across …