Infectious Disease

Bacterial Infection

Latest AI and machine learning research in bacterial infection for healthcare professionals.

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Showing 1461-1480 of 4,598 articles

Beyond isolated cough events: AI-based tuberculosis screening through temporal analysis of cough sounds

Tuberculosis (TB) is a major global health challenge, with many cases remaining undiagnosed due to limited access to screening and diagnostic services. Artificial intelligence (AI) systems based on cough sound analysis offer a scalable and accessible approach to TB screening, but most previous studies have analysed isolated cough events, despite the possibility that diagnostically useful informati...

amR: an R package suite to predict antimicrobial resistance in bacterial pathogens

Motivation: Identifying bacterial antimicrobial resistance (AMR) is critical for diagnostics and treatment, but resistance is a complex trait arising from myriad mechanisms spanning multiple molecular scales. Existing computational approaches often function as black boxes and rarely explore cross-species or multi-drug patterns. We developed amR, an integrated R package suite that provides a comple...

The Patients' Voice in Clostridioides difficile Infection: Large Language Model-Assisted Thematic Analysis of Patient Testimonials

Background. Clostridioides difficile infection (CDI) imposes a burden that extends well beyond the gastrointestinal tract, yet existing outcome measur...

AllTheBacteria: a community resource empowers biology and discovers novel peptide antibiotics

Public microbial genomes encode an immense record of biological diversity, evolution and molecular function, but much of this information remains diff...

Clinical Impact, Diagnostic Performance, and Prognostic Implications of Plasma Metagenomic Next-Generation Sequencing in Solid Organ Transplant Recipients

Introduction: Plasma metagenomic next-generation sequencing (mNGS) may detect pathogens in solid organ transplant (SOT) recipients, but optimal patien...

Improving Generalizability in Whole-Cell Antibiotic Discovery Through Active Learning

Machine learning (ML) has accelerated molecular discovery, yet training models to generalize to out-of-distribution (OOD) chemical spaces remains fund...

Models trained with noisy genomes extend bacterial phenotype prediction into deep time

Predicting phenotype from genotype in extant organisms is increasingly tractable through the accumulation of genome sequences and the development of m...

DDTRN: Predicting Bacterial Transcriptional Regulatory Networks Based on Gene Sequences using Dual Descriptor

Accurate computational reconstruction of bacterial transcriptional regulatory network (TRN) from sequence information alone remains a fundamental chal...

Collective fluctuations underlying nanobody inhibitory activity targeting B. anthracis S-layers revealed by multiscale simulations

Nanobodies (Nbs) that depolymerize bacterial surface-layers (S-layers) offer a route to antivirulence therapeutics, but their mechanisms have been dif...

Optical flow reveals motility signatures for inferring pathogenic bacterial mixture compositions via temporal convolutional networks

With the rapid expansion of global food demand, aquaculture has become a critical pillar for future food security. However, aquaculture systems remain...

BATTLE-AMP: Benchmarking Antimicrobial Peptide Predictors

As antimicrobial resistance outpaces antibiotic development, antimicrobial peptides (AMPs) have emerged as a promising class of alternative antibacter...

Label-free Pathogen Identification with Microscopy Imaging and Deep Learning

Rapid and accurate pathogen identification is crucial for the clinical management of infectious diseases, particularly sepsis and severe respiratory i...

Host-derived bile acids drive dysbiosis by selecting bile-resistant epimerizing bacteria in inflammatory bowel disease

Microbial dysbiosis is a hallmark of inflammatory bowel diseases (IBD); however, its drivers and impact on disease pathophysiology are poorly understo...

Predicting optimal growth temperatures of bacteria using learned structural information from a single protein

Temperature is a fundamental determinant of bacterial physiology and ecology. Optimal growth temperature (OGT) is highly variable across species, cont...

AURA: Active-Response Attribution under Treatment Ambiguity in Bacterial Cytological Profiling

When a bacterial sample is exposed to several antibiotics, not every applied drug necessarily acts: if the organism is resistant to one of them, that ...

Jun 15 2026 2606.16477v1
A Deep Hypergraph Learning Model for Predicting Antimicrobial Combination Effects Across Bacterial Targets

Antimicrobial resistance (AMR) creates an urgent need for efficient strategies to identify effective antibacterial combinations. Combination therapy, ...

Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets

The rise of antibiotic resistance necessitates the discovery of antibacterial compounds with novel mechanisms of action (MoAs). Recent machine learnin...

Pairing Data Independent Acquisition and High-Resolution Full Scan for Fast Urinary Tract Infection Diagnosis

Background: Rapid and accurate identification of urinary tract infection (UTI) pathogens is critical for effective treatment and combating antimicrobi...

BacteReason: A Reasoning Model for Antimicrobial Resistance Prediction

The rapid global spread of antimicrobial resistance (AMR) has placed unprecedented pressure on clinical decision-making. Machine learning predictors o...

Multi-omic data fusion reveals the in vivo enzyme kinetics of Vibrio natriegens at the genome-scale

Vibrio natriegens is a halophilic, Gram-negative marine bacterium that is increasingly used in metabolic engineering applications due to its fast grow...

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