AIMC Topic: Bacterial Infections

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A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.

Nature communications
Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral ...

Machine learning in the clinical microbiology laboratory: has the time come for routine practice?

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: Machine learning (ML) allows the analysis of complex and large data sets and has the potential to improve health care. The clinical microbiology laboratory, at the interface of clinical practice and diagnostics, is of special interest for...

Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data.

PLoS computational biology
Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation...

Comparison of the Abbott Architect BRAHMS and the Biomérieux Vidas BRAHMS Procalcitonin Assays.

The journal of applied laboratory medicine
BACKGROUND: Procalcitonin (PCT) is a well-established marker for bacterial infection. Recently the US Food and Drug Administration approved the expanded use of this biomarker to guide clinical decisions for antibiotic treatment in patients with lower...

FT-IR Hyperspectral Imaging and Artificial Neural Network Analysis for Identification of Pathogenic Bacteria.

Analytical chemistry
Identification of microorganisms by Fourier transform infrared (FT-IR) spectroscopy is known as a promising alternative to conventional identification techniques in clinical, food, and environmental microbiology. In this study we demonstrate the appl...

Using preference learning for detecting inconsistencies in clinical practice guidelines: Methods and application to antibiotherapy.

Artificial intelligence in medicine
Clinical practice guidelines provide evidence-based recommendations. However, many problems are reported, such as contradictions and inconsistencies. For example, guidelines recommend sulfamethoxazole/trimethoprim in child sinusitis, but they also st...

Procalcitonin as Predictor of Bacterial Infection in Meconium Aspiration Syndrome.

American journal of perinatology
BACKGROUND: There is a lack of definite consensus on indications for initiating antibiotics in neonates with meconium aspiration syndrome (MAS), instigating researchers to search for a biomarker that can help differentiate MAS from MAS with bacterial...

Defining lower airway bacterial infection in children with chronic endobronchial disorders.

Pediatric pulmonology
BACKGROUND: Differentiating lower airway bacterial infection from possible upper airway contamination in children with endobronchial disorders undergoing bronchoalveolar lavage (BAL) is important for guiding management. A diagnostic bacterial load th...