Universal precautions

Genome-wide analysis of the invasive fungal pathogen Neopestalotiopsis reveals high genomic diversity, effector repertoires, and the assessment of fungicide resistance risks.

Neopestalotiopsis species (spp.) have recently emerged as major pathogens worldwide, causing leaf spot, fruit rot, and crown rot of strawberry, resulting in increased disease outbreaks and economic losses. Despite their increasing impact, there is a limited genomic resource for this pathogen group, constraining insights into pathogenic mechanisms and fungicide resistance. We conducted whole-genome...

Predicting sleep state from continuous positive airway pressure flow in patients with obstructive sleep apnea.

INTRODUCTION: The first line treatment for obstructive sleep apnea (OSA) is continuous positive airway pressure (CPAP). CPAP adherence is assessed by hours of mask usage per night. To understand whether patients using CPAP are sleeping while wearing their mask (and thus may benefit from therapy), we aimed to predict sleep from CPAP flow signals. METHODS: We developed a machine learning algorithm t...

Using deep learning to identify brain networks mediating cognitive and motor impairments in alcohol use disorder.

Alcohol Use Disorder (AUD), with a lifetime prevalence of 29.1% in the U.S., is associated with functional impairment affecting visuospatial working m...

Risk Prediction of Early-Onset Hepatocellular Carcinoma: Derivation and Validation in a Nationwide Young Adult Cohort.

BACKGROUND: The global incidence of early-onset hepatocellular carcinoma (eHCC) is increasing significantly; however, specific risk prediction tools f...

PickAMoo: LIDAR-enhanced mask R-CNN segmentation for precision weight estimation in dairy cattle using smartphone imaging.

Data on body weight, as well as objective measures of body condition and size, are essential for appropriate decision-making on farm level, for exampl...

Developing a Naïve Bayes risk classification machine learning algorithm to predict high viral load in a low-resource setting.

Access to routine viral load (VL) testing for people living with HIV (PLHIV) remains limited in many low-resource settings. There is a need for pragma...

Knowledge-Based Interpretation of Multi-Modal Clinical Findings: Evaluating a Local Agentic Bridge Between Worlds.

Contemporary clinical practice still produces unstructured data like free-text reports or scans, hindering automated interpretation by knowledge-based...

Application of Metagenomics and Artificial Intelligence for Pathogen Characterization in Domestic Animals and Epizootic Prediction: A Systematic Review and Meta-Analysis.

Sub-Saharan Africa suffers devastating animal health losses exceeding $20 billion each year. By combining metagenomics with artificial intelligence (A...

Optimizing hepatitis C diagnosis through reinforcement learning feature selection and multi-model machine learning evaluation.

Hepatitis C virus (HCV) infection remains a leading cause of liver cirrhosis and hepatocellular carcinoma globally, affecting approximately 50 million...

Unveiling Viral Escape Mechanisms With Machine Learning: A Transformative Approach to Mutation Analysis for SARS-CoV-2 and Beyond.

Persistent viruses like Influenza, HIV, and Coronavirus exemplify the challenge of viral escape, significantly hindering the development of long-lasti...

The One Health resistome: Integrating environmental, microbial, and human antimicrobial resistance surveillance and risk analysis in the digital age.

Antimicrobial resistance (AMR) and antibiotic resistance (ABR) represent one of the most pressing global health threats, driven by the complex interpl...

A real-time early warning system to anticipate respiratory disease outbreaks using transfer learning.

Respiratory disease outbreaks burden American healthcare systems with over one million hospitalizations annually, yet current surveillance systems lag...

A multi-class framework for face mask compliance detection using lightweight deep learning models.

The use of face mask compliance regarding compliance monitoring is important in health sensitive and surveillance driven environments. This paper has ...

Prediction of HIV-1 sensitivity to broadly neutralizing antibodies using statistical distribution sampling (SDS) technology.

Accurately predicting HIV-1 sensitivity to broadly neutralizing antibodies (bNAbs) is a critical step in advancing the development of effective therap...

Global whole-genome, phylodynamic, and machine-learning analysis of Glaesserella parasuis serovars 2, 5, and 12.

Glaesserella parasuis is a respiratory pathogen of swine and the causative agent of Glässer's disease. Among the 15 serotypes, serotypes 2, 5, and 12 ...

Use of on-farm culturing for clinical mastitis treatment decisions and antimicrobial use in Argentina.

Clinical mastitis (CM) is one of the main causes of antimicrobial use (AMU) in dairy cattle, and strategies that support selective therapy are essenti...

Explainable machine learning incorporating CHI3L1 enhances liver fibrosis staging in chronic hepatitis B: The CHILI multicenter study.

BACKGROUND: Identifying significant liver fibrosis (≥F2) is critical for initiating antiviral therapy in chronic hepatitis B (CHB). Chitinase-3-like p...

A Fluorescence Imaging- and Deep Learning-Based Approach for Detecting Hepatitis B Virus Integration into Host Genomes.

Hepatitis B virus (HBV) infection can lead to hepatocellular carcinoma, and HBV integration into the host genome is regularly observed in the liver of...

Large-scale cryptic proteome mining revealed potential phage-mediated host-pathogen genetic exchange in Mycobacterium tuberculosis.

BACKGROUND: Due to inevitable evolution, clinical strains of Mycobacterium tuberculosis (Mtb) exhibit distinct phenotypes and differ significantly fro...

Machine learning in diagnostic stewardship: A technical approach in improving diagnostic accuracy, optimizing antibiotic use in false positive CSF cultures.

Diagnostic stewardship emphasises ordering the right tests, at the right time for the patient and also promotes the judicious use of rapid and accurat...