AIMC Topic: Respiratory Tract Infections

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Stacking ensemble learning models diagnose pulmonary infections using host transcriptome data from metatranscriptomics.

Scientific reports
The prompt diagnosis of pulmonary infections with unknown etiology in patients in severe condition remains a challenge due to the lack of rapid and effective diagnostic methods. While metatranscriptomic sequencing offers a powerful approach, its clin...

Respiratory viral infections: when and where? A scoping review of spatiotemporal methods.

Journal of global health
BACKGROUND: Respiratory viral infections pose a substantial disease burden worldwide. Spatiotemporal techniques help identify transmission patterns of these infections, thereby supporting timely control and prevention efforts. We aimed to synthesise ...

Discrimination of Respiratory Tract Infections by a Reduced Graphene Oxide Array Modified with Metal-Organic Frameworks and Metal Phthalocyanines.

ACS nano
As a prevalent clinical condition, it is critical to distinguish between bacterial and viral respiratory tract infections given their pivotal role in guiding appropriate pharmaceutical interventions and preventing antibiotic misuse. Exhaled breath (E...

A clinical data-driven machine learning approach for predicting the effectiveness of piperacillin-tazobactam in treating lower respiratory tract infections.

BMC pulmonary medicine
BACKGROUND: In hospitalized patients, inadequate antibiotic dosage leading to bacterial resistance and increased antimicrobial use intensity due to overexposure to antibiotics are common problems. In the present study, we constructed a machine learni...

Non-experimental rapid identification of lower respiratory tract infections in patients with chronic obstructive pulmonary disease using multi-label learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Microbiological culture is a standard diagnostic test that takes a long time to identify lower respiratory tract infections (LRTI) in patients with chronic obstructive pulmonary disease (COPD). This study entailed the develo...

Fluorescence excitation-emission matrix spectroscopy combined with machine learning for the classification of viruses for respiratory infections.

Talanta
Significant efforts were currently being made worldwide to develop a tool capable of distinguishing between various harmful viruses through simple analysis. In this study, we utilized fluorescence excitation-emission matrix (EEM) spectroscopy as a ra...

Prediction of acute respiratory infections using machine learning techniques in Amhara Region, Ethiopia.

Scientific reports
Many studies have shown that infectious diseases are responsible for the majority of deaths in children under five. Among these children, Acute Respiratory Infections is the most prevalent illness and cause of death worldwide. Acute respiratory infec...

How AI Could Help Us in the Epidemiology and Diagnosis of Acute Respiratory Infections?

Pathogens (Basel, Switzerland)
Acute respiratory infections (ARIs) represent a significant global health burden, contributing to high morbidity and mortality rates, particularly in vulnerable populations. Traditional methods for diagnosing and tracking ARIs often face limitations ...

Integrating respiratory microbiome and host immune response through machine learning for respiratory tract infection diagnosis.

NPJ biofilms and microbiomes
At present, the diagnosis of lower respiratory tract infections (LRTIs) is difficult, and there is an urgent need for better diagnostic methods. This study enrolled 136 patients from 2020 to 2021 and collected bronchoalveolar lavage fluid (BALF) spec...

Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors.

Environmental monitoring and assessment
This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory dise...