[HTML][HTML] Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: A comprehensive review of COVID-19 detection

MS Islam, KF Hasan, HH Shajeeb, HK Rana… - AI Open, 2025 - Elsevier
This study presents a comprehensive review of the potential of multimodal deep learning
(DL) in medical diagnosis, using COVID-19 as a case example. Motivated by the success of …

Multimodal Marvels of Deep Learning in Medical Diagnosis: A Comprehensive Review of COVID-19 Detection

MS Islam, KF Hasan, HH Shajeeb, HK Rana… - arxiv preprint arxiv …, 2025 - arxiv.org
This study presents a comprehensive review of the potential of multimodal deep learning
(DL) in medical diagnosis, using COVID-19 as a case example. Motivated by the success of …

MuTCELM: An optimal multi-TextCNN-based ensemble learning for text classification

VK Agbesi, W Chen, SB Yussif, CC Ukwuoma, YH Gu… - Heliyon, 2024 - cell.com
Feature extraction plays a critical role in text classification, as it converts textual data into
numerical representations suitable for machine learning models. A key challenge lies in …

Arabic Short Text Analytics using Multivariate Filter Methods and ProdLDA Model

E Qais, MN Veena - 2024 Second International Conference on …, 2024 - ieeexplore.ieee.org
Research in the domain of Arabic short text analytics remains constrained. Although there
have been several research conducted on other languages, there is still a lack of …

A Novel CAD Framework with Visual and Textual Interpretability: Multimodal Insights for Predicting Respiratory Diseases

R Mukhlis, S Saleem, H Kwon… - … and Data Processing …, 2024 - ieeexplore.ieee.org
Generating textual interpretability using recent advancements in large language models
(LLMs) is crucial for enhancing the efficiency of comprehensive computer-aided diagnosis …