Infectious Disease

AI in Medical Questionnaires: Innovations, Diagnosis, and Implications.

This systematic review aimed to explore the current applications, potential benefits, and issues of artificial intelligence (AI) in medical questionnaires, focusing on its role in 3 main functions: assessment, development, and prediction. The global mental health burden remains severe. The World Health Organization reports that >1 billion people worldwide experience mental disorders, with the prev...

Technologies for the point-of-care diagnosis of malaria: a scoping review.

BACKGROUND: Malaria continues to pose a significant health challenge, particularly in low-resource settings (LRS), where access to reliable and timely diagnostics is often limited. In this context, point-of-care (POC) in vitro diagnostics (IVDs) play a key role in supporting early detection and treatment. The aim of this scoping review was to better understand the landscape of malaria IVD technolo...

Classification of COVID-19, Long COVID, and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near-Real-Time Monitoring Component.

BACKGROUND: Heart rate variability (HRV) is a validated biomarker of autonomic and inflammatory regulation, and has been associated with both acute CO...

Machine learning model for prediction of coronavirus disease 2019 within 6 months after three doses of BNT162b2 in Hong Kong.

INTRODUCTION: We aimed to develop a machine learning (ML) model to predict the risk of coronavirus disease 2019 (COVID-19) among three-dose BNT162b2 v...

Utilizing Machine Learning to Improve Neutralization Potency of an HIV-1 Antibody Targeting the gp41 N-Heptad Repeat.

The N-heptad repeat (NHR) of the HIV-1 gp41 prehairpin intermediate (PHI) is an attractive potential vaccine target with high sequence conservation ac...

Enhancing early mortality prediction for sepsis-associated acute respiratory distress syndrome patients via optimized machine learning algorithm: development and multiple databases' validation of the SAFE-Mo.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is associated with high mortality, with sepsis accounts for 31-34% of cases. Given the global b...

Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: a prospective observational study.

OBJECTIVE: The heterogeneous nature of sepsis renders determining its underlying causes difficult, which may delay diagnosis and intervention. VitalCa...

Attention-driven UNet enhancement for accurate segmentation of bacterial spore outgrowth in microscopy images.

Analyzing microscopy images of large growing cell samples using traditional methods is a complex and time-consuming process. In this work, we have dev...

Disease entity impacts muscle wasting in the ICU with COVID-19 patients losing muscle nearly twice as fast.

Muscle loss in critically ill patients, particularly during prolonged ICU stays, poses significant challenges to recovery and long-term outcomes. ICU-...

Leveraging viral genome sequences and machine learning models for identification of potentially selective antiviral agents.

Viral genome sequencing provides valuable information for antiviral development, yet its integration with machine learning for virtual screening remai...

Prediction of Sepsis after Endourologic Kidney Stone Surgery: A Machine Learning Approach.

Sepsis secondary to urinary tract infection after kidney stone surgery is associated with considerable morbidity. Limited research examines the use o...

Machine learning model for daily prediction of pediatric sepsis using Phoenix criteria.

BACKGROUND: Early sepsis diagnosis is essential for initiating prompt treatment, preventing the progression of organ failure, and improving the surviv...

PSO-SVM optimized dielectric barrier discharge plasma for energy-efficient degradation of sulfamethoxazole in wastewater.

Conventional treatment methods struggle to effectively eliminate sulfamethoxazole (SMX) from wastewater due to its persistent aromatic structure and s...

Cancer vaccines and the future of immunotherapy.

Vaccines have had a major impact on the control of infectious disease, most recently by helping to combat the COVID-19 pandemic. Prophylactic cancer v...

Genomic and machine learning approaches to predict antimicrobial resistance in .

UNLABELLED: is a multidrug-resistant pathogen, which poses a major challenge to clinical management due to its increasing resistance to common antibi...

Changes in Epidemiological Characteristics of Varicella and Breakthrough Cases in Ningbo, China, From 2010 to 2023: Surveillance Study.

BACKGROUND: Varicella is a prevalent respiratory infectious disease. Continuous monitoring is essential to understand evolving epidemiological pattern...

Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.

Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare setting...

Divergence in a eukaryotic transcription factor's co-TF dependence involves multiple intrinsically disordered regions.

Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet its mechanism, evolution, and regulatory impact are...

Improved Prediction of Drug-Protein Interactions through Physics-Based Few-Shot Learning.

Accurate prediction of drug-protein interactions is crucial for drug discovery. Due to the bottleneck of traditional scoring functions, many machine l...

Predicting 14-day readmission in middle-aged and elderly patients with pneumonia using emergency department data: a multicentre retrospective cohort study with a survival machine learning approach.

OBJECTIVES: Unplanned pneumonia readmissions increase patient morbidity, mortality and healthcare costs. Among pneumonia patients, the middle-aged and...