AIMC Topic:
SARS-CoV-2
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An evaluation of two commercial deep learning-based information retrieval systems for COVID-19 literature.
Journal of the American Medical Informatics Association : JAMIA
Jan 15, 2021
The COVID-19 pandemic has resulted in a tremendous need for access to the latest scientific information, leading to both corpora for COVID-19 literature and search engines to query such data. While most search engine research is performed in academia...
DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes.
Proceedings of the National Academy of Sciences of the United States of America
Jan 12, 2021
Information about macromolecular structure of protein complexes and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully aut...
UniProt: the universal protein knowledgebase in 2021.
Nucleic acids research
Jan 8, 2021
The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over ...
Mouse Genome Database (MGD): Knowledgebase for mouse-human comparative biology.
Nucleic acids research
Jan 8, 2021
The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the community model organism knowledgebase for the laboratory mouse, a widely used animal model for comparative studies of the genetic and genomic basis for human health and disease. ...
Cytomegalovirus and Severe Acute Respiratory Syndrome Coronavirus 2 Co-infection in Renal Transplants: A Retrospective Study from a Single Center.
Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Jan 1, 2021
There is a scarcity of data regarding the impact of cytomegalovirus (CMV) infection complicating the coronavirus disease-2019 (COVID-19) course. The objective of the study was to explore the clinical profile and outcome of CMV co-infection with COVID...
[Forefront of AI Applications for COVID-19 Imaging Diagnosis].
Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics
Jan 1, 2021
The intra- and inter-observer variability in diagnosis of thoracic CT images may affect the diagnosis of COVID-19. Therefore, several studies have been reported to develop artificial intelligence (AI) approaches using deep learning (DL) and radiomics...
Technology-Enabled and Artificial Intelligence Support for Pre-Visit Planning in Ambulatory Care: Findings From an Environmental Scan.
Annals of family medicine
Jan 1, 2021
PURPOSE: Pre-visit planning (PVP) is believed to improve effectiveness, efficiency, and experience of care, yet numerous implementation barriers exist. There are opportunities for technology-enabled and artificial intelligence (AI) support to augment...
Hierarchical convolutional models for automatic pneu-monia diagnosis based on X-ray images: new strategies in public health.
Annali di igiene : medicina preventiva e di comunita
Jan 1, 2021
CONCLUSIONS: Despite some limits, our findings support the notion that deep learning methods can be used to simplify the diagnostic process and improve disease management.
Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.
Advances in experimental medicine and biology
Jan 1, 2021
Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into...
Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A Review.
Current medical imaging
Jan 1, 2021
BACKGROUND: This paper provides a systematic review of the application of Artificial Intelligence (AI) in the form of Machine Learning (ML) and Deep Learning (DL) techniques in fighting against the effects of novel coronavirus disease (COVID-19).
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