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 …

Artificial Intelligence (AI) and infectious diseases prediction have recently experienced a
common development and advancement. Machine learning (ML) apparition, along with …

Abstract In this research, Attention Induced Multi-head Convolutional Neural Network
Organization using MobileNetv1 Transfer Learning and COVID-19 Diagnosis using Jellyfish …

Mycoplasma pneumoniae pneumonia (MPP) poses significant diagnostic challenges in
pediatric healthcare, especially in regions like China where it's prevalent. We introduce …

Deep learning methods have significantly improved medical image analysis, particularly in
detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some …

Background Leishmaniasis, an illness caused by protozoa, accounts for a substantial
number of human fatalities globally, thereby emerging as one of the most fatal parasitic …

Purpose The study aims to develop an unsupervised framework using COVGANs to learn
better visual representations of COVID-19 from unlabeled X-ray and CT scans. Methods We …

The COVID-19 pandemic, driven by the rapid evolution of the SARS-CoV-2 virus, presents
ongoing challenges to global public health. SARS-CoV-2 is characterized by rapidly …

Abstract Background/Objectives: The COVID-19 pandemic has created an urgent need for
rapid and accurate diagnosis to facilitate timely treatment and control spread. However, the …

Artificial Intelligence and infectious diseases prediction have recently experienced a
common development and advancement. Machine learning apparition, along with deep …