Infectious Disease

An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction.

Impedance-based biosensing has emerged as a critical technology for high-sensitivity biomolecular detection, yet traditional approaches often rely on bulky, costly impedance analyzers, limiting their portability and usability in point-of-care applications. Addressing these limitations, this paper proposes an advanced biosensing system integrating a Silicon Nanowire Field-Effect Transistor (SiNW-FE...

STI/HIV risk prediction model development-A novel use of public data to forecast STIs/HIV risk for men who have sex with men.

A novel automatic framework is proposed for global sexually transmissible infections (STIs) and HIV risk prediction. Four machine learning methods, namely, Gradient Boosting Machine (GBM), Random Forest (RF), XG Boost, and Ensemble learning GBM-RF-XG Boost are applied and evaluated on the Demographic and Health Surveys Program (DHSP), with thirteen features ultimately selected as the most predicti...

The clinical features and risk factors of coagulopathy associated with cefoperazone/sulbactam: a nomogram prediction model.

BACKGROUND: Cefoperazone/sulbactam (CPZ/SAM) is an important treatment option for infections caused by multidrug-resistant gram-negative bacteria. How...

Sulforaphane as a promising anti-caries agents: inhibitory effects on and caries control in a rat model.

Dental caries has been one of the most prevalent diseases globally over the last few decades, threatening human oral and general health. The most crit...

Active Microrobots for Dual Removal of Biofilms via Chemical and Physical Mechanisms.

Bacterial biofilms are complex multicellular communities that adhere firmly to solid surfaces. They are widely recognized as major threats to human he...

Machine Learning-Enhanced Bacteria Detection Using a Fluorescent Sensor Array with Functionalized Graphene Quantum Dots.

Pathogenic bacteria are the source of many serious health problems, such as foodborne diseases and hospital infections. Timely and accurate detection ...

Functional antimicrobial peptide-loaded 3D scaffolds for infected bone defect treatment with AI and multidimensional printing.

Infection is the most prevalent complication of fractures, particularly in open fractures, and often leads to severe consequences. The emergence of ba...

Deaf futurity: designing and innovating hearing aids.

One of the tenets of a posthuman vision is the eradication of disability through technology. Within this site of 'no future', as Alison Kafer describe...

Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to purine metabolism-associated genes.

Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents a continuum that may progress from mild systemic ...

Fibrosis and inflammatory activity diagnosis of chronic hepatitis C based on extreme learning machine.

The traditional diagnosis of chronic hepatitis C usually relies on liver biopsy. Diagnosing chronic hepatitis C based on serum indices provides a non-...

Employing a low-code machine learning approach to predict in-hospital mortality and length of stay in patients with community-acquired pneumonia.

Community-acquired pneumonia (CAP) is associated with high mortality rates and often results in prolonged hospital stays. The potential of machine lea...

Noninvasive diagnosis of significant liver fibrosis in patients with chronic hepatitis B using nomogram and machine learning models.

This study aims to construct and validate noninvasive diagnosis models for evaluating significant liver fibrosis in patients with chronic hepatitis B ...

Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis.

This study investigates the impact of patient stress on COVID-19 screening. An attempt was made to measure the level of anxiety of individuals underta...

Use of Machine Learning to Assess the Management of Uncomplicated Urinary Tract Infection.

IMPORTANCE: Uncomplicated urinary tract infection (UTI) is a common indication for outpatient antimicrobial therapy. National guidelines for the manag...

Exploring happiness factors with explainable ensemble learning in a global pandemic.

Happiness is a state of contentment, joy, and fulfillment, arising from relationships, accomplishments, and inner peace, leading to well-being and pos...

Prediction of sepsis among patients with major trauma using artificial intelligence: a multicenter validated cohort study.

BACKGROUND: Sepsis remains a significant challenge in patients with major trauma in the ICU. Early detection and treatment are crucial for improving o...

Machine learning identifies remodeling patterns in human lung extracellular matrix.

Organ function depends on the three-dimensional integrity of the extracellular matrix (ECM). The structure resulting from the location and association...

Assessing the environmental determinants of micropollutant contamination in streams using explainable machine learning and network analysis.

Even at trace concentrations, micropollutants, including pesticides and pharmaceuticals, pose considerable ecological risks, and the increasing presen...

A prediction approach to COVID-19 time series with LSTM integrated attention mechanism and transfer learning.

BACKGROUND: The prediction of coronavirus disease in 2019 (COVID-19) in broader regions has been widely researched, but for specific areas such as urb...

Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks.

Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to...