Infectious Disease

A fourfold pathogen reference ontology suite.

BACKGROUND: Infectious diseases remain a critical global health challenge, and the integration of standardized ontologies plays a vital role in managing related data. The Infectious Disease Ontology (IDO) and its extensions, such as the Coronavirus Infectious Disease Ontology (CIDO), are essential for organizing and disseminating information related to infectious diseases. The COVID-19 pandemic hi...

Deep Learning-Assisted Rapid Bacterial Classification Based on Raman Spectroscopy of Bacteria Lysed by Acoustically Driven Fiber-Tip Vibration.

Rapid and accurate identification of bacterial pathogens is critical for effective clinical decision-making and combating antibiotic resistance. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) offers a powerful method for rapid, label-free bacterial identification. Conventional methods rely on surface molecular structures for identification, yet the richer and unique...

Deep Learning in Antimicrobial Peptide Prediction.

Antimicrobial peptides (AMPs) have garnered significant attention from researchers as effective alternatives to antibiotics. In recent years, deep lea...

Predicting SARS-CoV-2-specific CD4 and CD8 T-cell responses elicited by inactivated vaccines in healthy adults using machine learning models.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlights the importance of monitoring immune response...

MTMedFormer: multi-task vision transformer for medical imaging with federated learning.

Deep learning has revolutionized medical imaging, improving tasks like image segmentation, detection, and classification, often surpassing human accur...

Progress in the application research of cervical cancer screening developed by artificial intelligence in large populations.

Cervical cancer stands out among various cancers due to its potential for prevention and eradication, mainly through vaccination and proactive screeni...

Deep Learning-Enhanced Hand-Driven Spatial Encoding Microfluidics for Multiplexed Molecular Testing at Home.

The frequent global outbreaks of viral infectious diseases have significantly heightened the urgent demand for molecular testing at home. However, the...

Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets.

The treatment of sepsis is challenging due to unclear mechanisms. Propionate is increasingly seen as critical to sepsis pathophysiology by bridging gu...

Citywide metagenomic surveillance of food centres reveals local microbial signatures and antibiotic resistance gene enrichment.

The distribution of microorganisms in built environments with high human traffic, such as food centres, can potentially have a significant impact on p...

Machine learning approaches to dissect hybrid and vaccine-induced immunity.

BACKGROUND: The spread of SARS-CoV-2 Omicron variant and its subvariants, highly transmissible but responsible of milder disease, has increased unrepo...

The application and discovery of animal models in enterovirus research.

Enterovirus infection remains a significant global public health challenge, causing severe diseases such as hand, foot, and mouth disease (HFMD) and m...

Early detection of emerging SARS-CoV-2 Variants from wastewater through genome sequencing and machine learning.

Genome sequencing from wastewater enables accurate and cost-effective identification of SARS-CoV-2 variants. However, existing computational pipelines...

Gut microbiota composition is related to anxiety and aggression scores in companion dogs.

There is mounting evidence for a link between behaviour and the gut microbiome in animal and human health. However, the role of the gut microbiome in ...

Predictive models of influenza A virus lethal disease yield insights from ferret respiratory tract and brain tissues.

Collection of systemic tissues from influenza A virus (IAV)-infected ferrets at a fixed timepoint post-inoculation represents a frequent component of ...

CombiANT reader: Deep learning-based automatic image processing tool to robustly quantify antibiotic interactions.

Antibiotic resistance is a severe danger to human health, and combination therapy with several antibiotics has emerged as a viable treatment option fo...

Role of artificial intelligence in ICU therapeutic decision-making for severe infections.

PURPOSE OF REVIEW: To discuss current and future role of artificial intelligence in predicting severe infections and supporting decisions on antibioti...

Machine Learning and DIA Proteomics Reveal New Insights into Carbapenem Resistance Mechanisms in .

The emergence of Carbapenem-resistant (CRKP) represents a major public health concern, primarily driven by its ability to evade a wide range of antib...

Bifunctional Phyto-Synthesized Nano Silver for Mitigating Salinity-Induced Dormancy and Associated Fungal Infections During Seed Germination in Brassica juncea with Integration of Machine Learning-Based Predictive Modeling.

Salinity-induced dormancy associated with fungal infection during germination in plants is the major contributor to abiotic and biotic stress, leading...

Unlocking potent anti-tuberculosis natural products through structure-activity relationship analysis.

Tuberculosis (TB) remains a world health problem due to the high number of affected individuals, high mortality rates, prolonged treatment durations, ...

Discrimination of Dengue Diseases in Children Using Surface-Enhanced Raman Spectroscopy Coupled with Machine Learning Approaches.

This study introduces a novel approach to dengue diagnostics by leveraging surface-enhanced Raman spectroscopy (SERS) coupled to machine learning. Thi...