AIMC Topic:
SARS-CoV-2
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ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features.
Briefings in bioinformatics
Jan 17, 2022
MOTIVATION: The Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. As of CASP14, there are 79 global QA methods, and a minority of 39 residue-level QA methods with very few of them working on protein complex...
Focus on technology: surgical selfies, ransomware attacks, AI-assisted mental health care.
CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
Jan 10, 2022
A Deep Learning based Solution (Covi-DeteCT) Amidst COVID-19.
Current medical imaging
Jan 1, 2022
BACKGROUND: The whole world has been severely affected due to the COVID-19 pandemic. The rapid and large-scale spread has caused immense pressure on the medical sector hence increasing the chances of false detection due to human errors and mishandlin...
Detection of COVID-19 Infection in CT and X-ray images using transfer learning approach.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2022
BACKGROUND: The infection caused by the SARS-CoV-2 (COVID-19) pandemic is a threat to human lives. An early and accurate diagnosis is necessary for treatment.
Accuracy of the Traditional COVID-19 Phone Triaging System and Phone Triage-Driven Deep Learning Model.
Journal of primary care & community health
Jan 1, 2022
OBJECTIVES: During the COVID-19 pandemic, a quick and reliable phone-triage system is critical for early care and efficient distribution of hospital resources. The study aimed to assess the accuracy of the traditional phone-triage system and phone tr...
A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
There is still an urgent need to develop effective treatments to help minimize the cases of severe COVID-19. A number of tools have now been developed and applied to address these issues, such as the use of non-contrast chest computed tomography (CT)...
A Hybrid Protocol for Identifying Comorbidity-Based Potential Drugs for COVID-19 Using Biomedical Literature Mining, Network Analysis, and Deep Learning.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has spread on an unprecedented scale around the globe. Despite of 141,975 published papers on COVID-19 and several hundreds of new studies carri...
An interpretable multi-task system for clinically applicable COVID-19 diagnosis using CXR.
Journal of X-ray science and technology
Jan 1, 2022
BACKGROUND: With the emergence of continuously mutating variants of coronavirus, it is urgent to develop a deep learning model for automatic COVID-19 diagnosis at early stages from chest X-ray images. Since laboratory testing is time-consuming and re...
Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Like an article narrative is deemed by an editor and referees to be worthy of being a version of record on acceptance as a publication, so must the underpinning data also be scrutinized before passing it as a version of record. Indeed without the und...
Optimized chest X-ray image semantic segmentation networks for COVID-19 early detection.
Journal of X-ray science and technology
Jan 1, 2022
BACKGROUND: Although detection of COVID-19 from chest X-ray radiography (CXR) images is faster than PCR sputum testing, the accuracy of detecting COVID-19 from CXR images is lacking in the existing deep learning models.
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