Special Issue "Artificial Intelligence and Healthcare Analytics for COVID-19"

Submission Deadline: 25 January 2021 (closed)
Guest Editors
Dr. Senthilkumar Mohan, Vellore Institute of Technology, India.
Dr. Mohammad Tabrez Quasim, University of Bisha, Saudi Arabia.
Dr. Ayoub khan, University of Bisha, Saudi Arabia.


In the era of Machine learning, deep learning has extreme growth in the healthcare and medical field. Using AI / ML techniques in hospitals, providing optimal solution becomes important. This aims to find new challenges and overcome the difficulties of novel models/techniques by using AI. However, around the globe corona disease increases every day, prediction and prevention become essential and based on AI techniques like image classification/ segmentation, object detection, healthcare analytics techniques become unavoidable. This calls for bringing novel ideas in artificial intelligence, deep learning, neural networks, machine learning, and healthcare analytics based on COVID-19 which will provide values for researchers and scientists with advanced AI techniques. The proposal aims to collect innovative and unpublished work that focused on Machine learning, Deep learning, Healthcare analytics techniques, and models for COVID-19. This special issue provides an opportunity for researchers around the globe to share their novel ideas in an exciting area.

• Machine learning and deep learning-based techniques with medical image analyses.
• Machine learning and deep learning-based heart and lung infection.
• Deep learning and Neural networks for lung infections.
• Machine learning and deep learning techniques for prediction/ forecasting Artificial Intelligence methods for COVID -19 diagnostic models.
• Detection of COVID-19 disease based on Healthcare analytics and Machine learning features.
• Healthcare analytics and deep learning-based on CT images and other image processing models.
• Prediction / preventions models for hospitals.
• Early prevention/prediction of COVID-19 based on advanced machine learning and deep learning techniques.
• Novel methods with AI for COVID -19.

Published Papers
  • Prediction Models for COVID-19 Integrating Age Groups, Gender, and Underlying Conditions
  • Abstract The COVID-19 pandemic has caused hundreds of thousands of deaths, millions of infections worldwide, and the loss of trillions of dollars for many large economies. It poses a grave threat to the human population with an excessive number of patients constituting an unprecedented challenge with which health systems have to cope. Researchers from many domains have devised diverse approaches for the timely diagnosis of COVID-19 to facilitate medical responses. In the same vein, a wide variety of research studies have investigated underlying medical conditions for indicators suggesting the severity and mortality of, and role of age groups and gender on,… More
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  • CNN Ensemble Approach to Detect COVID-19 from Computed Tomography Chest Images
  • Abstract In January 2020, the World Health Organization declared a global health emergency concerning the spread of a new coronavirus disease, which was later named COVID-19. Early and fast diagnosis and isolation of COVID-19 patients have proven to be instrumental in limiting the spread of the disease. Computed tomography (CT) is a promising imaging method for fast diagnosis of COVID-19. In this study, we develop a unique preprocessing step to resize CT chest images to a fixed size (256 × 256 pixels) that preserves the aspect ratio and reduces image loss. Then, we present a deep learning (DL) method to classify… More
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  • Deep Learning Approach for COVID-19 Detection in Computed Tomography Images
  • Abstract With the rapid spread of the coronavirus disease 2019 (COVID-19) worldwide, the establishment of an accurate and fast process to diagnose the disease is important. The routine real-time reverse transcription-polymerase chain reaction (rRT-PCR) test that is currently used does not provide such high accuracy or speed in the screening process. Among the good choices for an accurate and fast test to screen COVID-19 are deep learning techniques. In this study, a new convolutional neural network (CNN) framework for COVID-19 detection using computed tomography (CT) images is proposed. The EfficientNet architecture is applied as the backbone structure of the proposed network,… More
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