Infectious Disease

AI-Based Denoising for Simulated Dose Reduction in Pediatric Chest Radiography: A Prospective Multicenter Evaluation of Image Quality and Diagnostic Performance.

RATIONALE AND OBJECTIVES: Radiation dose reduction in pediatric chest radiography is a clinical priority due to increased radiosensitivity and cumulative lifetime risk. However, substantial dose reduction may degrade image quality and compromise diagnostic performance. Artificial intelligence (AI)-based denoising has emerged as a potential solution, although robust prospective multicenter validati...

Machine Learning-Based Magnetocardiography Model Aids in Diagnosing Non-ST-Segment Elevation Acute Coronary Syndrome in Acute Chest Pain.

BACKGROUND: Non-ST-segment elevation acute coronary syndrome (NSTE-ACS) is a leading cause of acute chest pain in clinical practice. Magnetocardiography (MCG) is a non-invasive and rapid functional imaging technique with high sensitivity to early, subtle electrophysiological changes associated with myocardial ischemia. AIMS: To develop and validate a machine learning (ML)-based diagnostic model fo...

Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.

There is considerable interest in training machine learning (ML) models on genomic data that achieve clinical grade diagnostic accuracy. Many successf...

Influenza forecasting method based on dual-chan nel feature fusion of VMD decomposition.

Accurate influenza forecasting is critical for timely public health responses and resource allocation. To address challenges such as strong non-statio...

Predicting the evolutionary and structural compensation in Tat ARM region across HIV-1 groups using machine learning approach.

Predicting cervical cancer among women living with HIV/AIDS at public health facilities in a resource-limited setting in Ethiopia using machine learning analysis.

Association between platelet-albumin-bilirubin score and 30-day in-hospital mortality in patients with sepsis: evidence from a large database and machine learning modeling.

Whole-genome sequencing and machine learning reveal candidate genomic features associated with Listeria monocytogenes persistence in two ice cream facilities.

Listeria monocytogenes is a major foodborne pathogen responsible for listeriosis. Ice cream has emerged as an important vehicle for L. monocytogenes t...

The promise of AlphaFold for gene structure annotation.

Most new genomes lack annotation, automated methods are error-prone, and few genomes are ever manually curated due to time and cost. Protein structure...

Dissecting serum polyclonal antibody escape to SARS-CoV-2 variants by deep mutational learning.

Deep mutational scanning (DMS) has been extensively used to investigate how single-position mutations in the receptor-binding domain (RBD) affect bind...

Leveraging large language models for metabolic engineering design.

Establishing efficient cell factories involves a continuous process of trial and error due to metabolic complexity. This complexity makes predicting e...

PhaBOX2: an enhanced web server for discovering and analyzing viral contigs in metagenomic data.

Metagenomic sequencing has transformed virus discovery; however, downstream bioinformatic analyses for viral identification, classification, and host ...

YeastSAM: A Deep Learning Model for Accurate Segmentation of Yeast Cells.

Cell segmentation-the process of defining cell outlines in microscopy images-is essential for quantitative image analysis. Segmentation of budding yea...

Classifying Post-COVID "Brain Fog" Patients and Identifying Key ROIs via Graph Neural Network Model.

Brain fog has raised significant public health concerns as a common neurocognitive impairment in the post-COVID-19 condition, involving memory loss, p...

Updates on tuberculosis imaging.

Tuberculosis (TB) remains a leading infectious cause of morbidity and mortality worldwide, and major diagnostic and therapeutic challenges persist des...

Advances in molecular diagnostic strategies during the SARS-CoV-2 pandemic.

INTRODUCTION: The SARS-CoV-2 pandemic provided critical insights into pandemic preparedness. The community spread can be slowed down or contained thro...

In silico discovery of nanobody binders to a G-protein coupled receptor using AlphaFold-Multimer.

Antibodies are central mediators of the adaptive immune response, and they are powerful research tools and therapeutics. Antibody discovery requires s...

SyntheMol-RL: a flexible reinforcement learning framework for designing easily synthesizable antibiotics.

The rise of antibiotic-resistant pathogens such as Staphylococcus aureus has created an urgent need for new antibiotics. Generative artificial intelli...

Decision-support system for live detection of Leishmania parasites from microscopic images with deep learning.

Emerging technologies and AI-assisted tools in cardiopulmonary monitoring.

PURPOSE OF REVIEW: Cardiopulmonary monitoring is fundamental to critical care, yet traditional approaches rely on simplified thresholds that capture o...