Infectious Disease

Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time.

With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first real-time, reagent-free, portable analysis platform for viral detection in liquid saliva, using COVID-19 as a proof-of-concept. We show that vibration...

Leveraging convolutional neural networks and hashing techniques for the secure classification of monkeypox disease.

The World Health Organization declared a state of emergency in 2022 because of monkeypox. This disease has raised international concern as it has spread beyond Africa, where it is endemic. The global community has shown attention and solidarity in combating this disease as its daily increase becomes evident. Various skin symptoms appear in people infected with this disease, which can spread easily...

Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.

This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infection, identifying candidate hub genes and potential d...

Adult Code Sepsis: A Narrative Review of its Implementation and Impact.

This narrative review explores the implementation and impact of sepsis code protocols, an urgent intervention strategy designed to improve clinical ou...

Integrated machine learning to predict the prognosis of lung adenocarcinoma patients based on SARS-COV-2 and lung adenocarcinoma crosstalk genes.

Viruses are widely recognized to be intricately associated with both solid and hematological malignancies in humans. The primary goal of this research...

Novel large empirical study of deep transfer learning for COVID-19 classification based on CT and X-ray images.

The early and highly accurate prediction of COVID-19 based on medical images can speed up the diagnostic process and thereby mitigate disease spread; ...

Predicting the risk of pulmonary infection after kidney transplantation using machine learning methods: a retrospective cohort study.

PURPOSE: Pulmonary infection is the most common and serious complication after kidney transplantation that affects the survival of the transplanted ki...

Machine learning driven metal oxide-based portable sensor array for on-site detection and discrimination of mycotoxins in corn sample.

Cereals, grains, and feedstuffs are prone to contamination by fungi during various stages from growth to storage. These fungi may produce harmful myco...

Machine-Learning Approach to Identify Potential Dengue Virus Protease Inhibitors: A Computational Perspective.

The global prevalence of dengue virus (DENV), a widespread flavivirus, has led to varied epidemiological impacts, economic burdens, and health consequ...

Presurgery and postsurgery: advancements in artificial intelligence and machine learning models for enhancing patient management in infective endocarditis.

Infective endocarditis (IE) is a severe infection of the inner lining of the heart, known as the endocardium. It is characterized by a range of sympto...

The infection post flexible UreteroreNoscopy (I-FUN) predictive model based on machine learning: a new clinical tool to assess the risk of sepsis post retrograde intrarenal surgery for kidney stone disease.

PURPOSE: To create a machine-learning model for estimating the likelihood of post-retrograde intrarenal surgery (RIRS) sepsis.

Artificial intelligence in predicting pathogenic microorganisms' antimicrobial resistance: challenges, progress, and prospects.

The issue of antimicrobial resistance (AMR) in pathogenic microorganisms has emerged as a global public health crisis, posing a significant threat to ...

Is ChatGPT-4 a Reliable Tool in Autoimmune Hepatitis?

INTRODUCTION: Artificial intelligence-based chatbots offer a potential avenue for delivering personalized counseling to patients with autoimmune hepat...

Essential blood molecular signature for progression of sepsis-induced acute lung injury: Integrated bioinformatic, single-cell RNA Seq and machine learning analysis.

In this study, we aimed to identify an essential blood molecular signature for chacterizing the progression of sepsis-induced acute lung injury using ...

Machine learning accelerates the discovery of epitope-based dual-bioactive peptides against skin infections.

OBJECTIVES: Skin injuries and infections are an inevitable part of daily human life, particularly with chronic wounds, becoming an increasing socioeco...

A deep learning algorithm that aids visualization of femoral neck fractures and improves physician training.

PURPOSE: Missed fractures are the most common radiologic error in clinical practice, and erroneous classification could lead to inappropriate treatmen...

sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms.

BACKGROUND: Bacterial small regulatory RNA (sRNA) plays a crucial role in cell metabolism and could be used as a new potential drug target in the trea...

Rapid and accurate bacteria identification through deep-learning-based two-dimensional Raman spectroscopy.

Surface-enhanced Raman spectroscopy (SERS) offers a distinctive vibrational fingerprint of the molecules and has led to widespread applications in med...

Impacts of micro/nano plastics on the ecotoxicological effects of antibiotics in agricultural soil: A comprehensive study based on meta-analysis and machine learning prediction.

Micro/nano plastics (M/NPs) and antibiotics, as widely coexisting pollutants in environment, pose serious threats to soil ecosystem. The purpose of th...

Developing a machine learning model with enhanced performance for predicting COVID-19 from patients presenting to the emergency room with acute respiratory symptoms.

Artificial Intelligence is playing a crucial role in healthcare by enhancing decision-making and data analysis, particularly during the COVID-19 pande...