AIMC Topic: COVID-19

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AI-driven deep convolutional neural networks for chest X-ray pathology identification.

Journal of X-ray science and technology
BACKGROUND: Chest X-ray images are widely used to detect many different lung diseases. However, reading chest X-ray images to accurately detect and classify different lung diseases by doctors is often difficult with large inter-reader variability. Th...

Digital Healthcare for Airway Diseases from Personal Environmental Exposure.

Yonsei medical journal
Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, health products and services have expanded by the use and development of artificial intelligence, mob...

Detecting Racial/Ethnic Health Disparities Using Deep Learning From Frontal Chest Radiography.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to assess racial/ethnic and socioeconomic disparities in the difference between atherosclerotic vascular disease prevalence measured by a multitask convolutional neural network (CNN) deep learning model using fronta...

Artificial Intelligence in Vaccine and Drug Design.

Methods in molecular biology (Clifton, N.J.)
Knowledge in the fields of biochemistry, structural biology, immunological principles, microbiology, and genomics has all increased dramatically in recent years. There has also been tremendous growth in the fields of data science, informatics, and ar...

Precision Medicine: Using Artificial Intelligence to Improve Diagnostics and Healthcare.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The continued generation of large amounts of data within healthcare-from imaging to electronic medical health records to genomics and multi-omics -necessitates tools and methods to parse and interpret these data to improve healthcare outcomes. Artifi...

The diagnostic performance of deep-learning-based CT severity score to identify COVID-19 pneumonia.

The British journal of radiology
OBJECTIVE: To determine the diagnostic accuracy of a deep-learning (DL)-based algorithm using chest computed tomography (CT) scans for the rapid diagnosis of coronavirus disease 2019 (COVID-19), as compared to the reference standard reverse-transcrip...

UBNet: Deep learning-based approach for automatic X-ray image detection of pneumonia and COVID-19 patients.

Journal of X-ray science and technology
BACKGROUND: Analysis of chest X-ray images is one of the primary standards in diagnosing patients with COVID-19 and pneumonia, which is faster than using PCR Swab method. However, accuracy of using X-ray images needs to be improved.

Computer-aided COVID-19 diagnosis and a comparison of deep learners using augmented CXRs.

Journal of X-ray science and technology
BACKGROUND: Coronavirus Disease 2019 (COVID-19) is contagious, producing respiratory tract infection, caused by a newly discovered coronavirus. Its death toll is too high, and early diagnosis is the main problem nowadays. Infected people show a varie...

Vaccine Design by Reverse Vaccinology and Machine Learning.

Methods in molecular biology (Clifton, N.J.)
Reverse vaccinology (RV) is the state-of-the-art vaccine development strategy that starts with predicting vaccine antigens by bioinformatics analysis of the whole genome of a pathogen of interest. Vaxign is the first web-based RV vaccine prediction m...

Fighting COVID-19 with Artificial Intelligence.

Methods in molecular biology (Clifton, N.J.)
The development of vaccines for the treatment of COVID-19 is paving the way for new hope. Despite this, the risk of the virus mutating into a vaccine-resistant variant still persists. As a result, the demand of efficacious drugs to treat COVID-19 is ...