Infectious Disease

Latest AI and machine learning research in infectious disease for healthcare professionals.

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Lightweight convolutional neural network for chest X-ray images classification.

In this study, we developed a lightweight and rapid convolutional neural network (CNN) architecture ...

Evaluation of rapid detection methods for H5N1 virus using biosensors: An AI-based study.

High mortality and zoonotic potential predispose the H5N1 avian influenza virus as a critical threat...

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics.

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge ...

Dynamics of infectious disease mathematical model through unsupervised stochastic neural network paradigm.

The viruses has spread globally and have been impacted lives of people socially and economically, wh...

A hybrid model for monthly runoff forecasting based on mixed signal processing and machine learning.

Monthly runoff forecasting plays a critically supportive role in water resources planning and manage...

Severity prediction markers in dengue: a prospective cohort study using machine learning approach.

BACKGROUND: Dengue virus causes illnesses with or without warning indicators for severe complication...

Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques.

Hepatocellular carcinoma (HCC) represents a significant health burden in Egypt, largely attributable...

Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines.

Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity ...

-targeted AI-driven vaccines: a paradigm shift in gastric cancer prevention.

, a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cance...

Machine Learning Models as Early Warning Systems for Neonatal Infection.

Neonatal infections pose a significant threat to the health of newborns. Associated morbidity and mo...

Machine learning predicts pulmonary Long Covid sequelae using clinical data.

Long COVID is a multi-systemic disease characterized by the persistence or occurrence of many sympto...

Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis.

Antimicrobial peptides (AMPs) are a promising class of antimicrobial drugs due to their broad-spectr...

A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants.

Understanding which viral variants evade neutralization is crucial for improving antibody-based trea...

Current update on the neurological manifestations of long COVID: more questions than answers.

Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting wi...

Two-step graph propagation for incomplete multi-view clustering.

Incomplete multi-view clustering addresses scenarios where data completeness cannot be guaranteed, d...

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