Infectious Disease

Healthcare-associated ventriculitis and meningitis in a neuro-ICU: Incidence and risk factors selected by machine learning approach.

PURPOSE: To define the incidence of healthcare-associated ventriculitis and meningitis (HAVM) in the neuro-ICU and to identify HAVM risk factors using tree-based machine learning (ML) algorithms.

Total phenolic and flavonoid contents and antioxidant activity of ginger ( Rosc.) rhizome, callus and callus treated with some elicitors.

The present study was aimed at determining total phenolic and flavonoid contents and studying the antioxidant activity of ginger ( Rosc.) rhizome and callus, 6-gingerol and 6-shogaol and callus treated with elicitors. Petroleum ether (PE) and chloroform: methanol (1:1, v/v) (CM) extracts were prepared by maceration. Highest total phenolic content was obtained from the CM extract (60.34 ± 0.43 mg g...

Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network.

Because influenza is a contagious respiratory illness that seriously threatens public health, accurate real-time prediction of influenza outbreaks may...

Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical- Approach Combining Experiments and Machine Learning.

Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in ...

Computational Prediction of Sigma-54 Promoters in Bacterial Genomes by Integrating Motif Finding and Machine Learning Strategies.

Sigma factor, as a unit of RNA polymerase holoenzyme, is a critical factor in the process of gene transcriptional regulation. It recognizes the specif...

Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms.

BACKGROUND: Since early antimicrobial therapy is mandatory in septic patients, immediate diagnosis and distinction from non-infectious SIRS is essenti...

Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.

We present a cost-effective and portable platform based on contact lenses for noninvasively detecting Staphylococcus aureus, which is part of the huma...

A new scheme for strain typing of methicillin-resistant Staphylococcus aureus on the basis of matrix-assisted laser desorption ionization time-of-flight mass spectrometry by using machine learning approach.

Methicillin-resistant Staphylococcus aureus (MRSA), one of the most important clinical pathogens, conducts an increasing number of morbidity and morta...

The Discovery of an Iridium(III) Dimer Complex as a Potent Antibacterial Agent against Non-Replicating Mycobacterium smegmatis.

Novel agents are urgently needed to rapidly kill drug-resistant . Noble metal complexes, particularly polypyridyl iridium complexes serving as therape...

Predicting urinary tract infections in the emergency department with machine learning.

BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine c...

A novel triterpenoid 16-hydroxy betulinic acid isolated from attributes multi-faced pharmacological activities.

The aerial parts of extensively used ethnomedicinal plant (Burm. f.) Robinson growing wild in Bangladesh were investigated to isolate and characteriz...

Using machine-learning to optimize phase contrast in a low-cost cellphone microscope.

Cellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computat...

Molecular identification and in vitro antifungal susceptibility of Scedosporium complex isolates from high-human-activity sites in Mexico.

The genus Scedosporium is a complex of ubiquitous moulds associated with a wide spectrum of clinical entities, with high mortality principally in immu...

The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison.

INTRODUCTION: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control met...

Development and Validation of a Natural Language Processing Tool to Identify Patients Treated for Pneumonia across VA Emergency Departments.

BACKGROUND: Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processin...

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires.

The adaptive immune system recognizes antigens an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interr...

Predicting treatment outcome of drug-susceptible tuberculosis patients using machine-learning models.

Tuberculosis (TB) is a deadly contagious disease and a serious global health problem. It is curable but due to its lengthy treatment process, a patien...

Using Machine Learning and a Combination of Respiratory Flow, Laryngeal Motion, and Swallowing Sounds to Classify Safe and Unsafe Swallowing.

OBJECTIVE: The aim of this research was to develop a swallowing assessment method to help prevent aspiration pneumonia. The method uses simple sensors...

Enhanced prediction of recombination hotspots using input features extracted by class specific autoencoders.

In yeast and in some mammals the frequencies of recombination are high in some genomic locations which are known as recombination hotspots and in the ...

Antifungal activity of chitinase II against Colletotrichum falcatum Went. causing red rot disease in transgenic sugarcane.

We evaluated transgenic lines of sugarcane modified with the barley chitinase class-II gene to create resistance against the red rot causative agent C...