AIMC Topic: COVID-19

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Accurate and fast clade assignment via deep learning and frequency chaos game representation.

GigaScience
BACKGROUND: Since the beginning of the coronavirus disease 2019 pandemic, there has been an explosion of sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, making it the most widely sequenced virus in the history. S...

[Chest imaging-based artificial intelligence in the diagnosis of coronavirus disease 2019 and prospects for future research].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Artificial intelligence (AI) has been applied increasingly in the medical field during the past 5 years. Within respiratory medicine, chest imaging AI is one of the relevant hotspots, commonly trained to identify pulmonary nodules/lung tumors, tuberc...

Outpatient Robotic surgery: Considerations for the Anesthesiologist.

Advances in anesthesia
A shortage of inpatient beds and nurses during the coronavirus disease 2019 pandemic has lent priority to safe same-day discharge after surgery. The minimally invasive nature of robotic surgery has allowed an increasing number of procedures to be don...

Surveys Aimed at General Citizens of the US and Japan About Their Attitudes Toward Electronic Medical Data Handling - 10 Years Change, Before and After Covid-19.

Studies in health technology and informatics
OBJECTIVES: To clarify the views of the general population of two countries (US and Japan), concerning handling of their medical records electronically, disclosure of the name of disease, secondary usage of information, compiling their records into a...

Diagnostic performance of corona virus disease 2019 chest computer tomography image recognition based on deep learning: Systematic review and meta-analysis.

Medicine
BACKGROUND: To analyze the diagnosis performance of deep learning model used in corona virus disease 2019 (COVID-19) computer tomography(CT) chest scans. The included sample contains healthy people, confirmed COVID-19 patients and unconfirmed suspect...

DeepHisCoM: deep learning pathway analysis using hierarchical structural component models.

Briefings in bioinformatics
Many statistical methods for pathway analysis have been used to identify pathways associated with the disease along with biological factors such as genes and proteins. However, most pathway analysis methods neglect the complex nonlinear relationship ...

HLAncPred: a method for predicting promiscuous non-classical HLA binding sites.

Briefings in bioinformatics
Human leukocyte antigens (HLA) regulate various innate and adaptive immune responses and play a crucial immunomodulatory role. Recent studies revealed that non-classical HLA-(HLA-E & HLA-G) based immunotherapies have many advantages over traditional ...

CNGOD-An improved convolution neural network with grasshopper optimization for detection of COVID-19.

Mathematical biosciences and engineering : MBE
The world is facing the pandemic situation due to a beta corona virus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The disease caused by this virus known as Corona Virus Disease 2019 (COVID-19) has affected the entire world. Th...

DeepLUCIA: predicting tissue-specific chromatin loops using Deep Learning-based Universal Chromatin Interaction Annotator.

Bioinformatics (Oxford, England)
MOTIVATION: The importance of chromatin loops in gene regulation is broadly accepted. There are mainly two approaches to predict chromatin loops: transcription factor (TF) binding-dependent approach and genomic variation-based approach. However, neit...

Deformable attention (DANet) for semantic image segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep learning based medical image segmentation is currently a widely researched topic. Attention mechanism used with deep networks significantly benefit semantic segmen-tation tasks. The recent criss-cross-attention module captures global self-attent...