Infectious Disease

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

8,053 articles
Stay Ahead - Weekly Infectious Disease research updates
Subscribe
Browse Categories
Showing 988-1008 of 8,053 articles
ResGloTBNet: An interpretable deep residual network with global long-range dependency for tuberculosis screening of sputum smear microscopy images.

Tuberculosis is a high-mortality infectious disease. Manual sputum smear microscopy is a common and ...

Point-annotation supervision for robust 3D pulmonary infection segmentation by CT-based cascading deep learning.

Infected region segmentation is crucial for pulmonary infection diagnosis, severity assessment, and ...

A numerical treatment through Bayesian regularization neural network for the chickenpox disease model.

OBJECTIVES: The current research investigations designates the numerical solutions of the chickenpox...

Unsupervised machine learning clustering approach for hospitalized COVID-19 pneumonia patients.

BACKGROUND: Identification of distinct clinical phenotypes of diseases can guide personalized treatm...

Integration of machine learning and meta-analysis reveals the behaviors and mechanisms of antibiotic adsorption on microplastics.

Microplastics (MPs) can adsorb antibiotics (ATs) to cause combined pollution in the environment. Res...

A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.

Accurate, real-time forecasts of influenza hospitalizations would facilitate prospective resource al...

Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics.

The rediscovery of known drug classes represents a major challenge in natural products drug discover...

Systematic collection, annotation, and pattern analysis of viral vaccines in the VIOLIN vaccine knowledgebase.

BACKGROUND: Viral vaccines have been proven significant in protecting us against viral diseases such...

Artificial intelligence: a useful tool in active tuberculosis screening among vulnerable groups in Romania - advantages and limitations.

INTRODUCTION: Despite advances in diagnostic technologies for tuberculosis (TB), global control of t...

Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to ...

MSCMamba: Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module.

Antimicrobial peptides (AMPs) have important developmental prospects as potential candidates for nov...

Deep learning-driven bacterial cytological profiling to determine antimicrobial mechanisms in .

Tuberculosis (TB), caused by , remains a significant global health threat, affecting an estimated 10...

Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation.

Transient receptor potential vanilloid 4 (TRPV4) is a calcium-permeable cation channel critical for ...

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

BACKGROUND: Mumps is a viral respiratory disease characterized by facial swelling and transmitted th...

Future prospective of AI in drug discovery.

Drug discovery and development is very expensive and long with an inferior success rate. It is quite...

Two-stage CNN-based framework for leukocytes classification.

Leukocytes are pivotal markers in health, crucial for diagnosing diseases like malaria and viral inf...

Autoregressive exogenous neural structures for synthetic datasets of olive disease control model with fractional Grünwald-Letnikov solver.

A fundamental element of the Mediterranean diet, olive oil is abundant in heart-healthy monounsatura...

Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides.

Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however...

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.

This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to pre...

Eye-tracking dataset of endoscopist-AI teaming during colonoscopy: Retrospective and real-time acquisition.

Recent studies have demonstrated that integrating AI into colonoscopy procedures significantly impro...

Browse Categories