Infectious Disease

Computational identification and multi-level validation of marine fungal metabolites as potent inhibitors of Acinetobacter baumannii GuaB.

Lightweight attention enhanced YOLOv11 for accurate multi class detection of brinjal diseases.

The cultivation of brinjal is seriously affected by various pathogens which affect crop yield and qu...

Artificial intelligence in microbiology: implications for metagenomics, diagnostics, and AMR surveillance.

Artificial intelligence (AI) is now a key player in modern microbiology, as it enables high-resoluti...

Smart hydrogels for overcoming cancer multidrug resistance.

Multidrug resistance (MDR) remains the principal impediment to curative oncology, driven by complex ...

Restoring auditory discrimination in noise: mismatch negativity evidence for a deep neural network-based denoising system in hearing aids.

BACKGROUND: Understanding speech in noise is a primary challenge for individuals with sensorineural ...

Artificial intelligence at the frontlines: Emerging infectious and parasitic diseases in the digital era.

Emerging infectious diseases are one of the most significant threats to global health, driven by man...

Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.

PURPOSE: Lung cancer is the leading cause of cancer-related mortality worldwide, yet its underlying ...

AI-driven fungicide design: From target identification to field application.

Plant pathogenic fungi severely threaten global agriculture, causing substantial yield losses in sta...

Macroecological processes impact Australian soil resistomes and climatically stable regions with anthropogenic activities serve as ARG hotspots.

Soil antibiotic resistance genes (ARGs) pose a global health threat, but a critical knowledge gap re...

Identifying mitochondria-related signatures for tuberculosis diagnosis through machine learning on single-cell transcriptomics data and experimental verification.

Tuberculosis (TB) remains a major cause of infectious disease mortality. Early diagnosis is crucial ...

The emergence of superficial dermatophytosis due to Trichophyton indotineae and Trichophyton mentagrophytes genotypes VII and II* in New York: a need for comprehensive testing approaches.

We report a rapid increase in dermatophyte infections in New York City and surrounding counties from...

Tripleknock: predicting lethal effect of three-gene knockout in bacteria by deep learning.

Investigating the lethal effect of multi-gene knockout is essential for discovering novel antibiotic...

LobePrior segments lung lobes on computed tomography images in the presence of severe abnormalities.

The development of robust algorithms for lung and lobe segmentation is essential for diagnosing and ...

Multidimensional Trends and AI-Based Forecasts of HIV Incidence in Korea, 1985-2024.

Integrative bioinformatics and machine learning identify shared molecular mechanisms and diagnostic biomarkers between Helicobacter pylori infection and atrial fibrillation.

BACKGROUND: Helicobacter pylori (H. pylori) infection and atrial fibrillation(AF) are major global h...

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

BACKGROUND: The recombinant production of Pseudomonas aeruginosa exotoxin A (ETA), a critical compon...

A multilayer 2D material plasmonic metasurface terahertz biosensor with machine learning optimization for high-sensitivity tuberculosis detection.

Tuberculosis (TB) remains a leading global infectious disease, with over 10.6 million new cases annu...

Smart diagnostics: Leveraging artificial intelligence for accurate at-home COVID-19 testing.

Reverse transcriptase polymerase chain reaction (RT-PCR), the reference standard for COVID-19 diagno...

Optimization of Zanthoxylum bungeanum essential oil extraction based on response surface methodology and machine learning with activity evaluation.

This study extracted Zanthoxylum bungeanum essential oil via steam distillation, with the extraction...

Investigating the potential risk of nicotine exposure on glioblastoma: Integrating Mendelian randomization and network toxicology analysis.

OBJECTIVE: To investigate the potential risk of nicotine exposure on glioblastoma multiforme (GBM). ...

Predicting hepatocellular carcinoma in people with hepatitis B: a comparison between Cox proportional hazard and machine learning models.

BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldw...