AI Medical Compendium Topic:
COVID-19

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Strong semantic segmentation for Covid-19 detection: Evaluating the use of deep learning models as a performant tool in radiography.

Radiography (London, England : 1995)
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
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)
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
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)
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
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
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
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...

Deep Transfer Learning for COVID-19 Detection and Lesion Recognition Using Chest CT Images.

Computational and mathematical methods in medicine
Starting from December 2019, the global pandemic of coronavirus disease 2019 (COVID-19) is continuously expanding and has caused several millions of deaths worldwide. Fast and accurate diagnostic methods for COVID-19 detection play a vital role in co...

LCSB-inception: Reliable and effective light-chroma separated branches for Covid-19 detection from chest X-ray images.

Computers in biology and medicine
According to the World Health Organization, an estimate of more than five million infections and 355,000 deaths have been recorded worldwide since the emergence of the coronavirus disease (COVID-19). Various researchers have developed interesting and...