Infectious Disease

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 diagnosis, is time-consuming, resource-intensive, and costly. Rapid antigen tests address these limitations but rely on visual interpretation, which may reduce diagnostic performance. This study evaluated the performance of artificial intelligence (AI) for interpreting at-home COVID-19 lateral flow antige...

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 process optimized using Response Surface Methodology (RSM) and machine learning techniques. The results indicated that the optimal conditions predicted by RSM were a distillation time of 92 min, an ultrasonic time of 25 min, and a liquid-solid ratio of 11.6 mL/g, yielding a predicted extraction rat...

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). METHODS: A two-sample Mendelian randomization (MR)...

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 worldwide, with chronic hepatitis B virus (HBV) infectio...

Machine learning for early detection and prediction of sepsis: explainability and key sepsis biomarkers representation-A systematic review.

OBJECTIVE: To systematically review machine learning-based sepsis prediction studies, examining model explainability and the extent to which explanati...

S3F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network.

Convolutional Neural Networks (CNNs) have become a cornerstone of medical image analysis due to their proficiency in learning hierarchical spatial fea...

Mechanistic Design of Graphdiyne-Based Multimodal Sensing Integrating Machine Learning and Photothermal Dynamics for Precision Recognition and On-Demand Inactivation.

Rapid and accurate detection of pathogenic bacteria remains essential for infection control and timely treatment. Here, we report a graphdiyne (GDY)-b...

Evaluating Public Sentiment on Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Compared With Other Mental Health Disorders From Posts on X (Formerly Known as Twitter): Longitudinal Analysis.

BACKGROUND: Neurodevelopmental disorders, especially attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), have seen a m...

Multimodal Learning with Privileged Report Supervision for Generalizable Tuberculosis Detection on Chest Radiographs.

K-STAMM: a knowledge-enhanced spatial - temporal attention model with multimodal fusion for pneumonia prediction.

Precise prediction of pneumonia remains a challenge mainly because effective integration of clinical data that are highly heterogeneous is mandatory. ...

Machine learning prediction of antibiotic resistance in Gram-negative pneumonia: a clinical-genomic integrated model.

Comparative evaluation of machine learning models for predicting COVID-19 vaccine uptake in U.S. adults.

Clinical evaluation of an AI-based pneumonia detection system on chest CT: a qualitative and quantitative analysis.

An interpretable deep learning framework for predictive modeling of postoperative infections in ICU patients.

A significant proportion of intensive care unit (ICU) patients undergo surgical procedures, and some may develop postoperative infections. Accurately ...

Valorization of turkey cruor through peptic hydrolysis: peptidomic and machine learning approaches for the identification of antimicrobial peptides.

The slaughterhouse blood remains an underexploited by-product with promising potential for producing natural antimicrobial agents. This study investig...

Ischaemia in tuberculous meningitis: update on pathophysiology, clinical predictors and management.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is a severe manifestation of Mycobacterium tuberculosis infection, associated with high mortality and ...

Simulation-based inference captures non-Markovian effects as exemplified in protein production kinetics through cell division.

Inferring protein production kinetics in dividing cells is complicated by protein inheritance from the mother cell. For instance, fluorescence measure...

Machine-Learning Source Apportionment of Particulate Pollution Aids Urban Emission Regulations.

Reducing urban particulate pollution is essential for improving air quality and reducing health risks. Achieving this objective requires accurate iden...

Healthcare-associated infections in Italian long-term care facilities: a machine learning analysis of a 12-month cohort.

OBJECTIVES: To estimate the incidence of healthcare-associated infections (HAIs) in Italian long-term care facilities (LTCFs) and to evaluate whether ...

Parent Questions About Childhood Hearing Loss: An Evaluation of ChatGPT Response Accuracy, Completeness, and Repeatability.

PURPOSE: We aimed to assess the responses to parent questions about childhood hearing loss that were generated by two generative artificial intelligen...