AIMC Topic:
SARS-CoV-2

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Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders.

Briefings in bioinformatics
The COVID-19 pandemic is marked by the successive emergence of new SARS-CoV-2 variants, lineages, and sublineages that outcompete earlier strains, largely due to factors like increased transmissibility and immune escape. We propose DeepAutoCoV, an un...

A tailored machine learning approach for mortality prediction in severe COVID-19 treated with glucocorticoids.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
BACKGROUNDThe impact of severe COVID-19 pneumonia on healthcare systems highlighted the need for accurate predictions to improve patient outcomes. Despite the established efficacy of glucocorticoids (GCs), variable patient respons...

Analyzing factors of daily travel distances in Japan during the COVID-19 pandemic.

Mathematical biosciences and engineering : MBE
The global impact of the COVID-19 pandemic is widely recognized as a significant concern, with human flow playing a crucial role in its propagation. Consequently, recent research has focused on identifying and analyzing factors that can effectively r...

Deep Learning-Based Prediction of Daily COVID-19 Cases Using X (Twitter) Data.

Studies in health technology and informatics
Due to the importance of COVID-19 control, innovative methods for predicting cases using social network data are increasingly under attention. This study aims to predict confirmed COVID-19 cases using X (Twitter) social network data (tweets) and deep...

Sensor-Based Fuzzy Inference of COVID-19 Transmission Risk in Cruise Ships.

Studies in health technology and informatics
Cruise ships are densely populated ecosystems where infectious diseases can spread rapidly. Hence, early detection of infected individuals and risk assessment (RA) of the disease transmissibility are critical. Recent studies have investigated the lon...

Enhancing Pulmonary Embolism Detection in COVID-19 Patients Through Advanced Deep Learning Techniques.

Studies in health technology and informatics
The intersection of COVID-19 and pulmonary embolism (PE) has posed unprecedented challenges in medical diagnostics. The critical nature of PE and its increased incidence during the pandemic underline the need for improved detection methods. This stud...

Feasibility and Educational Value of Clinical Cases Generated Using Large Language Models.

Studies in health technology and informatics
In medical education, case-based learning (CBL) is a fundamental method for training healthcare professionals across different levels of expertise. This approach hinges on using authentic or fabricated clinical cases to bridge the gap between theoret...

Next-Generation Teleophthalmology: AI-enabled Quality Assessment Aiding Remote Smartphone-based Consultation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Blindness and other eye diseases are a global health concern, particularly in low- and middle-income countries like India. In this regard, during the COVID-19 pandemic, teleophthalmology became a lifeline, and the Grabi attachment for smartphone-base...