Infectious Disease

A Machine learning model for predicting sepsis based on an optimized assay for microbial cell-free DNA sequencing.

OBJECTIVE: To integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis.

A potential new way to facilitate HCV elimination: The prediction of viremia in anti-HCV seropositive patients using machine learning algorithms.

BACKGROUND AND STUDY AIMS: The present study was undertaken to design a new machine learning (ML) model that can predict the presence of viremia in hepatitis C virus (HCV) antibody (anti-HCV) seropositive cases.

Optimizing removal of antiretroviral drugs from tertiary wastewater using chlorination and AI-based prediction with response surface methodology.

Chemical and pharmaceutical chemicals found in water sources create substantial risks to human health and the environment. The presence of pharmaceuti...

Metrisor: A novel diagnostic method for metritis detection in cattle based on machine learning and sensors.

The Metrisor device has been developed using gas sensors for rapid, highly accurate and effective diagnosis of metritis. 513 cattle uteri were collect...

Antibiotic discovery with artificial intelligence for the treatment of infections.

UNLABELLED: Global challenges presented by multidrug-resistant infections have stimulated the development of new treatment strategies. We reported th...

Identification of Microorganism in Infected Wounds by Positively Charged Selective Sensor Array and Deep Learning Algorithm.

Microorganism are ubiquitous and intimately connected with human health and disease management. The accurate and fast identification of pathogenic mic...

Enhancing pneumonia prognosis in the emergency department: a novel machine learning approach using complete blood count and differential leukocyte count combined with CURB-65 score.

BACKGROUND: Pneumonia poses a major global health challenge, necessitating accurate severity assessment tools. However, conventional scoring systems s...

Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.

Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected a...

Prediction of hospital-acquired influenza using machine learning algorithms: a comparative study.

BACKGROUND: Hospital-acquired influenza (HAI) is under-recognized despite its high morbidity and poor health outcomes. The early detection of HAI is c...

Spatiotemporal models of dengue epidemiology in the Philippines: Integrating remote sensing and interpretable machine learning.

Previous dengue epidemiological analyses have been limited in spatiotemporal extent or covariate dimensions, the latter neglecting the multifactorial ...

Combining serum microRNAs and machine learning algorithms for diagnosing infectious fever after HSCT.

Infection post-hematopoietic stem cell transplantation (HSCT) is one of the main causes of patient mortality. Fever is the most crucial clinical sympt...

Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data.

Bats play a pivotal role in maintaining ecological balance, and studying their behaviors offers vital insights into environmental health and aids in c...

A machine learning model for the early diagnosis of bloodstream infection in patients admitted to the pediatric intensive care unit.

Bloodstream infection (BSI) is associated with increased morbidity and mortality in the pediatric intensive care unit (PICU) and high healthcare costs...

Flexible Conformally Bioadhesive MXene Hydrogel Electronics for Machine Learning-Facilitated Human-Interactive Sensing.

Wearable epidermic electronics assembled from conductive hydrogels are attracting various research attention for their seamless integration with human...

Data mining and machine learning in HIV infection risk research: An overview and recommendations.

In the contemporary era, the applications of data mining and machine learning have permeated extensively into medical research, significantly contribu...

Enhanced differential evolution algorithm for feature selection in tuberculous pleural effusion clinical characteristics analysis.

Tuberculous pleural effusion poses a significant threat to human health due to its potential for severe disease and mortality. Without timely treatmen...

Deciphering the Coevolutionary Dynamics of L2 β-Lactamases via Deep Learning.

L2 β-lactamases, serine-based class A β-lactamases expressed by , play a pivotal role in antimicrobial resistance (AMR). However, limited studies have...

Deciphering and predicting changes in antibiotic resistance genes during pig manure aerobic composting via machine learning model.

Livestock manure is one of the most important pools of antibiotic resistance genes (ARGs) in the environment. Aerobic composting can effectively reduc...

Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health...

Exploring Antiviral Drugs on Monolayer Black Phosphorene: Atomistic Theory and Explainable Machine Learning-Assisted Platform.

Favipiravir (FP) and ebselen (EB) belong to a diverse class of antiviral drugs known for their significant efficacy in treating various viral infectio...