Infectious Disease

Early prediction of septic shock in ICU patients using machine learning: development, external validation, and explainability with SHAP.

BACKGROUND: Septic shock is a severe and life-threatening complication of sepsis associated with high mortality. Early identification remains challenging due to the heterogeneous clinical presentation of patients, incomplete real-world ICU data, and the dynamic pathophysiological progression of sepsis. This study aimed to develop and externally validate machine learning (ML) models to predict the ...

Machine learning-assisted sensing platform for simultaneous and visual detection of tetracycline hydrochloride and ofloxacin.

Antibiotics are essential in modern medicine; however, their overuse and improper disposal have caused significant environmental contamination, which impacts aquatic systems, food chains, and ecosystems while posing serious risks to human health. Current antibiotic detection methods are typically confined to laboratories and require professional expertise, creating a gap for portable sensors suita...

Ergonomic handheld chip: An instrument-free RPA-CRISPR platform for rapid home self-testing.

Global outbreaks of viral infectious diseases underscore the urgent need for low-cost, instrument-free, and user-friendly molecular testing platforms ...

A deep learning approach to predicting hospitalized patients' SEIRD states using multimodal spatiotemporal data.

BACKGROUND AND OBJECTIVE: The increasing prevalence of hospital-acquired infections (HAIs) due to antimicrobial resistance presents a formidable chall...

Authors reply: "A risk-adjusted length of stay to evaluate severe community-acquired pneumonia (sCAP) outcomes: A machine learning analysis of 16,985 ICU admissions".

Development of an Explainable Machine Learning Model to Predict Mortality Risk in Sepsis Patients: Insights From a Real-World Clinical Data.

BACKGROUND: Sepsis is a life-threatening dysregulated host response to infection; early risk stratification is essential to guide intensive care. OBJE...

Identification and Validation of Key Genes Related to Arginine Methylation Modification in Sepsis Using Transcriptome Combined with Mendelian Randomization Analysis.

BACKGROUND: Patients with sepsis often exhibit a decrease in lymphatic numbers, which can be facilitated by protein arginine methyltransferase (PRMT)....

Influences of growth media and culture time on the SERS spectral patterns of three common pathogenic bacteria: a comparative analysis.

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful tool for clinical microorganism identification, offering significant advantages o...

Hybridized artificial intelligence system for reducing neonatal mortality in Nigeria.

BACKGROUND: Neonatal diseases represent the leading cause of death in Nigeria, ranking the country second globally in neonatal mortality rates. Early ...

Amplification-free detection of mycoplasma pneumoniae via CRISPR-Cas12a and deep learning-optimized crRNAs on a lateral flow platform.

Accurate and rapid diagnosis of Mycoplasma pneumoniae infection is essential for reducing its significant health burden. An amplification-free CRISPR-...

4-Hydroxy-2,5-dihydrothiazole derivatives as a new class of small-molecule antibiotics for MRSA: AI-integrated design, chemical synthesis and biological evaluation.

Staphylococcus aureus (S. aureus) is one of the most concerned Gram-positive bacteria due to its resistance to the commonly used antibiotics, methicil...

Machine learning for food flavor prediction and regulation: models, data integration, and future perspectives.

BACKGROUND: Flavor is a central attribute of food quality, shaping consumer preferences and market performance. Traditional evaluation methods, such a...

Microbial-mycotoxin interactions in food: A review of ecotoxicological implications and omics approaches for understanding detoxification mechanisms.

Mycotoxins, toxic secondary metabolites produced by fungi such as Aspergillus, Fusarium, and Penicillium, frequently contaminate food supplies, posing...

Hospital-acquired pneumonia: Past, present, and perspectives.

Hospital-acquired pneumonia (HAP) remains the most frequent and lethal hospital acquired infection, driving ICU mortality, prolonged length of stay, a...

Machine learning-enabled microfluidic ratiometric fluorescence sensor array based on lanthanide-gold nanoclusters for visual detection of multicomponent antibiotics.

The accumulation of multiple antibiotics in the environment poses severe threats to ecosystems and human health, demanding rapid, sensitive, and porta...

A rural-to-center artificial intelligence model for diagnosing Helicobacter pylori infection and premalignant gastric conditions using endoscopy images captured in routine practice.

Diagnosing Helicobacter pylori infection and premalignant gastric conditions typically requires 13C urea breath testing or histological assessment, wh...

The effect of autonomous mobile robots on improving endoscope reprocessing efficiency: a prospective comparative trial (with video).

BACKGROUND AND AIMS: Autonomous mobile robots (AMRs) have an increasingly wide range of medical applications. However, their use in endoscopy centers ...

Epigenome and interactome profiling uncovers principles of distal regulation in the barley genome.

Regulation of transcription initiation is the ground level of modulating gene expression during plant development. This process relies on interactions...

Machine learning prediction of multidrug-resistant urinary tract infections in brain and spinal cord injury patients: a dual-center validation study.

BACKGROUND AND OBJECTIVE: Multidrug-resistant urinary tract infections (MDR UTIs) are a growing concern in patients with brain and spinal cord injurie...

Cervical cancer diagnostics: non-coding RNAs and biosensors to AI-derived methods.

Cervical cancer ranks fourth in terms of cancer mortality among women. The most important risk factor for cervical cancer is infection with HPV 16 and...