AIMC Topic: COVID-19

Clear Filters Showing 61 to 70 of 2297 articles

Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study.

JMIR formative research
BACKGROUND: Serious pulmonary pathologies of infectious, viral, or bacterial origin are accompanied by inflammation and an increase in oxidative stress (OS). In these situations, biological measurements of OS are technically difficult to obtain, and ...

Analyzing the impact of COVID-19 on seasonal infectious disease outbreak detection using hybrid SARIMAX-LSTM model.

Journal of infection and public health
BACKGROUND: This study estimates the incidence of seasonal infectious diseases, including influenza, norovirus, severe fever with thrombocytopenia syndrome (SFTS), and tsutsugamushi disease, in the Republic of Korea from 2005 to 2023. It also examine...

Enhancing the understandings on SARS-CoV-2 main protease (M) mutants from molecular dynamics and machine learning.

International journal of biological macromolecules
While star drugs like Paxlovid have shown remarkable performance in combating SARS-CoV-2, we still face serious challenges such as viral mutants and resistance. In this study, we employ a computational framework combining molecular dynamics (MD) simu...

Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics.

Scientific reports
Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitative measurements, although they could be concepts vital to understand pathogen epidemiology. This study demonstrates that the relative synonymous codon ...

DeepATsers: a deep learning framework for one-pot SERS biosensor to detect SARS-CoV-2 virus.

Scientific reports
The integration of Artificial Intelligence (AI) techniques with medical kits has revolutionized disease diagnosis, enabling rapid and accurate identification of various conditions. We developed a novel deep learning model, namely DeepATsers based on ...

Low-cost algorithms for clinical notes phenotype classification to enhance epidemiological surveillance: A case study.

Journal of biomedical informatics
OBJECTIVE: Our study aims to enhance epidemic intelligence through event-based surveillance in an emerging pandemic context. We classified electronic health records (EHRs) from La Rioja, Argentina, focusing on predicting COVID-19-related categories i...

Aligning, Autoencoding and Prompting Large Language Models for Novel Disease Reporting.

IEEE transactions on pattern analysis and machine intelligence
Given radiology images, automatic radiology report generation aims to produce informative text that reports diseases. It can benefit current clinical practice in diagnostic radiology. Existing methods typically rely on large-scale medical datasets an...

AI-imputed and crowdsourced price data show strong agreement with traditional price surveys in data-scarce environments.

PloS one
Continuous access to up-to-date food price data is crucial for monitoring food security and responding swiftly to emerging risks. However, in many food-insecure countries, price data is often delayed, lacks spatial detail, or is unavailable during cr...

Knowledge Representation and Management in the Age of Long Covid and Large Language Models: a 2022-2023 Survey.

Yearbook of medical informatics
OBJECTIVES: To select, present, and summarize cutting edge work in the field of Knowledge Representation and Management (KRM) published in 2022 and 2023.

Virtual reality in drug design: Benefits, applications and industrial perspectives.

Current opinion in structural biology
Virtual reality (VR) is a tool which has transformative potential in domains which involve the visualization of complex 3D data such as structure-based drug design (SBDD), where it offers new ways to visualize and manipulate complex molecular structu...