AIMC Topic: COVID-19
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D3AI-Spike: A deep learning platform for predicting binding affinity between SARS-CoV-2 spike receptor binding domain with multiple amino acid mutations and human angiotensin-converting enzyme 2.
Computers in biology and medicine
Oct 25, 2022
The number of SARS-CoV-2 spike Receptor Binding Domain (RBD) with multiple amino acid mutations is huge due to random mutations and combinatorial explosions, making it almost impossible to experimentally determine their binding affinities to human an...
Pandemic disease detection through wireless communication using infrared image based on deep learning.
Mathematical biosciences and engineering : MBE
Oct 24, 2022
Rapid diagnosis to test diseases, such as COVID-19, is a significant issue. It is a routine virus test in a reverse transcriptase-polymerase chain reaction. However, a test like this takes longer to complete because it follows the serial testing meth...
Strong semantic segmentation for Covid-19 detection: Evaluating the use of deep learning models as a performant tool in radiography.
Radiography (London, England : 1995)
Oct 24, 2022
INTRODUCTION: With the increasing number of Covid-19 cases as well as care costs, chest diseases have gained increasing interest in several communities, particularly in medical and computer vision. Clinical and analytical exams are widely recognized ...
Assessing the Severity of COVID-19 Lung Injury in Rheumatic Diseases Versus the General Population Using Deep Learning-Derived Chest Radiograph Scores.
Arthritis care & research
Oct 21, 2022
OBJECTIVE: COVID-19 patients with rheumatic disease have a higher risk of mechanical ventilation than the general population. The present study was undertaken to assess lung involvement using a validated deep learning algorithm that extracts a quanti...
Kids' Emotion Recognition Using Various Deep-Learning Models with Explainable AI.
Sensors (Basel, Switzerland)
Oct 21, 2022
Human ideas and sentiments are mirrored in facial expressions. They give the spectator a plethora of social cues, such as the viewer's focus of attention, intention, motivation, and mood, which can help develop better interactive solutions in online ...
Automatic deep learning-based consolidation/collapse classification in lung ultrasound images for COVID-19 induced pneumonia.
Scientific reports
Oct 20, 2022
Our automated deep learning-based approach identifies consolidation/collapse in LUS images to aid in the identification of late stages of COVID-19 induced pneumonia, where consolidation/collapse is one of the possible associated pathologies. A common...
Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning.
Sensors (Basel, Switzerland)
Oct 19, 2022
COVID-19 has infected millions of people worldwide over the past few years. The main technique used for COVID-19 detection is reverse transcription, which is expensive, sensitive, and requires medical expertise. X-ray imaging is an alternative and mo...
Automated system for classification of COVID-19 infection from lung CT images based on machine learning and deep learning techniques.
Scientific reports
Oct 18, 2022
The objectives of our proposed study were as follows: First objective is to segment the CT images using a k-means clustering algorithm for extracting the region of interest and to extract textural features using gray level co-occurrence matrix (GLCM)...
Emotional-Health-Oriented Urban Design: A Novel Collaborative Deep Learning Framework for Real-Time Landscape Assessment by Integrating Facial Expression Recognition and Pixel-Level Semantic Segmentation.
International journal of environmental research and public health
Oct 15, 2022
Emotional responses are significant for understanding public perceptions of urban green space (UGS) and can be used to inform proposals for optimal urban design strategies to enhance public emotional health in the times of COVID-19. However, most emp...
Computer-aided diagnostic for classifying chest X-ray images using deep ensemble learning.
BMC medical imaging
Oct 15, 2022
BACKGROUND: Nowadays doctors and radiologists are overwhelmed with a huge amount of work. This led to the effort to design different Computer-Aided Diagnosis systems (CAD system), with the aim of accomplishing a faster and more accurate diagnosis. Th...
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