Text, radiological pictures, audio notes, video, and other types of multimedia healthcare data are all generated by today's smart healthcare system [1].The evolution of COVID-19 has resulted in an incremental rise in current healthcare data.The study of multimodal healthcare data on such a big scale has revealed both obstacles and potential.Thanks to artificial intelligence (AI) and, more specifically, deep learning (DL) algorithms, which have been widely used by researchers for handling massive amounts of epidemic data, predicting live epidemic crises, and initiating new research directions in the analysis of healthcare multimedia data [2].As a result, deep learning for multimedia healthcare data analysis is becoming a hot topic in multimedia and computer vision research.The call for papers attracted 54 submissions and after a rigorous review, 20 papers have been accepted for this special issue.A brief summary of papers in this special issue is presented in the following:The paper titled "A Novel Study for Automatic Twoclass Covid-19 Diagnosis (between Covid-19 and Healthy, Pneumonia) on X-ray Images using Texture Analysis and 2-D/3-D Convolutional Neural Networks" aims to diagnose COVID-19 early using X-ray images, automatic two-class classification was carried out in four different titles: COVID-19/Healthy, COVID-19 Pneumonia/Bacterial Pneumonia, COVID-19 Pneumonia/Viral Pneumonia, and COVID-19 Pneumonia/Other Pneumonia.In the study, besides using