Infectious Disease

Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.

pressure injuries are significant concern for ICU patients on mechanical ventilation. Early prediction is crucial for enhancing patient outcomes and reducing healthcare costs. This study aims to develop a predictive model using machine learning techniques, specifically XGBoost combined with SHAP, to identify key risk factors of pressure ulcers in this population. Utilizing the MIMIC-IV 2.2 databas...

Machine learning-based prediction of vesicoureteral reflux outcomes in infants under antibiotic prophylaxis.

We aimed to investigate the independent outcome predictors of continuous antibiotic prophylaxis (CAP) in vesicoureteral reflux, train a model to predict the outcome, and evaluate which infants should be referred for endoscopic vesicoureteral reflux correction in their first visits. A total of 225 infants ≤ 2 years of age with a diagnosis of vesicoureteral reflux between 2009 and 2022 were recruite...

Machine learning-based model for predicting all-cause mortality in severe pneumonia.

BACKGROUND: Severe pneumonia has a poor prognosis and high mortality. Current severity scores such as Acute Physiology and Chronic Health Evaluation (...

Systems biology of Haemonchus contortus - Advancing biotechnology for parasitic nematode control.

Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and economies worldwide. Of these worms, Haemonchus co...

Assessment for antibiotic resistance in : A practical and interpretable machine learning model based on genome-wide genetic variation.

() antibiotic resistance poses a global health threat. Accurate identification of antibiotic resistant strains is essential for the control of infect...

Machine learning analysis of magnetic covalent organic framework based heterostructures extracted intracellular metabolic fingerprint for direct hypervirulent Klebsiella pneumoniae prediction.

Hypervirulent Klebsiella pneumoniae (hvKP), known for its high virulence and epidemic potential, has emerged as a significant global public health thr...

Forewarning the seasonal dynamics of corn leafhopper and mollicutes through neural networks.

The corn leafhopper (CL), Dalbulus maidis (DeLong & Wolcott) (Hemiptera: Cicadellidae), has become the most important corn pest in Brazil and other co...

Exploring the role of breastfeeding, antibiotics, and indoor environments in preschool children atopic dermatitis through machine learning and hygiene hypothesis.

The increasing global incidence of atopic dermatitis (AD) in children, especially in Western industrialized nations, has attracted considerable attent...

A Review of In Silico Approaches for Discovering Natural Viral Protein Inhibitors in Aquaculture Disease Control.

Viral diseases pose a significant threat to the sustainability of global aquaculture, causing economic losses and compromising food security. Traditio...

Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.

Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress...

Urban change detection: assessing biophysical drivers using machine learning and Google Earth Engine.

Urban areas are experiencing rapid transformations, driven by population growth, economic development, and policy changes. Understanding and monitorin...

A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation.

Colorectal cancer (CRC) is a prevalent gastrointestinal tumor worldwide with high morbidity and mortality. Predicting the survival of CRC patients not...

Spatio-temporal epidemic forecasting using mobility data with LSTM networks and attention mechanism.

The outbreak of infectious diseases can have profound impacts on socio-economic balances globally. Accurate short-term forecasting of infectious disea...

Performance evaluation of reduced complexity deep neural networks.

Deep Neural Networks (DNN) have achieved state-of-the-art performance in medical image classification and are increasingly being used for disease diag...

Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM.

BACKGROUND: Chronic hepatitis B (CHB) is a common cause of liver cirrhosis (LC), a condition associated with an unfavourable prognosis. Therefore, tim...

Biofilm-mediated infections; novel therapeutic approaches and harnessing artificial intelligence for early detection and treatment of biofilm-associated infections.

A biofilm is a group of bacteria that have self-produced a matrix and are grouped together in a dense population. By resisting the host's immune syste...

Reducing hepatitis C diagnostic disparities with a fully automated deep learning-enabled microfluidic system for HCV antigen detection.

Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C (HCV) causing approximately 1 million deaths annua...

Evaluating the performance of random forest, support vector machine, gradient tree boost, and CART for improved crop-type monitoring using greenest pixel composite in Google Earth Engine.

The development of machine learning algorithms, along with high-resolution satellite datasets, aids in improved agriculture monitoring and mapping. Ne...

Development of machine learning-based differential diagnosis model and risk prediction model of organ damage for severe Mycoplasma pneumoniae pneumonia in children.

Severe Mycoplasma pneumoniae pneumonia (SMPP) poses significant diagnostic challenges due to its clinical features overlapping with those of other com...

Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques.

Predictive models for determining coronavirus disease 2019 (COVID-19) severity have been established; however, the complexity of the interactions amon...