Infectious Disease

An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries.

BACKGROUND: Worldwide, anemia in children under-five is a major public health issue, particularly in sub-Saharan Africa. Sub-Saharan Africa also has the highest burden of malaria. This study aimed to develop an ensemble machine learning model to estimate anemia burden and potential predictors in under-five children in malaria-endemic sub-Saharan African countries. METHOD: A cross-sectional study w...

Retraction: Advanced machine learning-guided optimization platform for high-yield soluble expression of Pseudomonas aeruginosa exotoxin A in engineered Escherichia coli strains.

Modelling climatic and temporal dynamics of dengue transmission in Bangladesh using deep learning models.

Dengue fever is a significant public health issue in tropical and subtropical areas, and predicting its spread is challenging due to the complex inter...

Geospatial-based surveillance of malaria risk in dar es salaam using a hybrid 3DCNN + LSTM and CA model.

Malaria remains a significant public health burden in tropical and subtropical regions, where the efficient identification and prediction of risk area...

[Chinese guideline for the diagnosis and treatment of hospital-acquired pneumonia and ventilator-associated pneumonia in adults (2026 edition): protocol].

This document serves as the protocol for the development of the Chinese Guideline for the Diagnosis and Treatment of Hospital-Acquired Pneumonia and V...

Genotypic-phenotypic concordance of Pasteurella multocida isolated from bovine respiratory disease cases.

Pasteurella multocida is a respiratory pathogen that is frequently isolated from cattle suffering from bovine respiratory disease (BRD), a leading cau...

Disparities in severe infection risk associated with systemic lupus erythematosus: evidence from a causal forest analysis.

OBJECTIVES: Severe infections are a primary cause of morbidity and premature mortality in patients with Systemic Lupus Erythematosus (SLE). Although S...

Classification of SARS-CoV-2 Variants Through the Epistatic Circos Plots with Convolutional Neural Networks.

The COVID-19 pandemic has profoundly affected global health, driven by the remarkable transmissibility and mutational adaptability of the SARS-CoV-2 v...

Integrated deep learning and multi-scale modeling for the discovery of pan-genotypic HCV NS5B polymerase inhibitors.

Chronic Hepatitis C Virus (HCV) infection remains a significant global health challenge, necessitating the development of pan-genotypic inhibitors to ...

DeepPepQSAR: all-in-one for comprehensively exploiting the vast molecular diversity space of bioactive peptide universe.

Peptide quantitative structure-activity relationship (PepQSAR) has attracted much attention in the bio- and cheminformatics communities as a well-esta...

FUO-PETMamba: a pet maximum-intensity-projection-based artificial intelligence framework for aetiological classification of fever of unknown origin with multicentre validation.

BACKGROUND: Fever of unknown origin (FUO) remains diagnostically challenging because of heterogeneous causes, non-specific clinical manifestations, an...

Modeling multidimensional perceived risk in HIV-related social media: a multi-label transformers framework with longitudinal analysis.

This paper presents a supervised multi-label framework for detecting multidimensional perceived risk in HIV-related Reddit discourse. A longitudinal c...

RRM2B is associated with low-level viremia during entecavir therapy in pediatric chronic hepatitis B and promotes profibrotic signaling in vitro.

BACKGROUND: Low-level viremia (LLV) during nucleos(t)ide analogue therapy for chronic hepatitis B (CHB) is clinically relevant, but its biological bas...

[Artificial intelligence in neuro-ophthalmology: prospects, challenges and countermeasures].

Neuro-ophthalmic disorders feature complex etiology. Certain ocular manifestations may hint at severe neurological diseases. Current clinical practice...

Deep Learning Enables Identification of Antimicrobial Peptides Through Mechanochromic Fingerprints.

Antimicrobial peptides (AMPs) are promising antibiotic alternatives, but their diverse modes of action make functional classification slow and labor-i...

Bionic Magnetic Nanorobots Combined with AI-Assisted Microscopic Imaging for Argonaute-Powered Multiplexed Foodborne Pathogens Detection.

Multiplexed and ultrasensitive identification of foodborne pathogens is crucial for food safety. However, conventional methods are limited by complex ...

Machine learning integration of tissue-specific metagenomic signatures for colorectal cancer diagnosis.

Colorectal cancer (CRC) represents a significant global health burden. Leveraging machine learning (ML) with metagenomic and tissue-specific data pres...

Prediction of future onset of allergic rhinitis and analysis of risk factors in children with food allergy during infancy.

UNLABELLED: The atopic march describes the progression from infantile food allergy (FA) to allergic rhinitis (AR) in later childhood. However, not all...

Artificial Intelligence for Cervical HPV Infection and Lesion Screening: A Cross-Sectional Analysis of Its Application Potential and Patient Satisfaction.

OBJECTIVE: This cross-sectional study aimed to explore the application potential of artificial intelligence (AI) in screening and diagnosing cervical ...

Advancing stress biotechnology for robust sustainable bioproduction.

Environmental stressors compromise the economic viability of microbial bioproduction, making enhanced microbial robustness essential. While traditiona...