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Clinical evaluation of a multiplex droplet digital PCR for diagnosing suspected bloodstream infections: a prospective study.

Frontiers in cellular and infection microbiology
BACKGROUND: Though droplet digital PCR (ddPCR) has emerged as a promising tool for early pathogen detection in bloodstream infections (BSIs), more studies are needed to support its clinical application widely due to different ddPCR platforms with dis...

Single-cell microbiota phenotyping reveals distinct disease and therapy-associated signatures in Crohn's disease.

Gut microbes
IgA-coated fractions of the intestinal microbiota of Crohn's disease (CD) patients have been shown to contain taxa that hallmark the compositional dysbiosis in CD microbiomes. However, the correlation between other cellular properties of intestinal b...

Host-microbe multi-omics and succinotype profiling have prognostic value for future relapse in patients with inflammatory bowel disease.

Gut microbes
Crohn's disease (CD) and ulcerative colitis (UC) are chronic relapsing inflammatory bowel disorders (IBD), the pathogenesis of which is uncertain but includes genetic susceptibility factors, immune-mediated tissue injury and environmental influences,...

Performance of an Algorithm Grading Surgery-Related Adverse Events According to the Clavien-Dindo Classification.

Annals of surgery
OBJECTIVE: To assess the performance of an algorithm for automated grading of surgery-related adverse events (AEs) according to Clavien-Dindo (C-D) classification.

Comparative analysis of kidney function prediction: traditional statistical methods vs. deep learning techniques.

Clinical and experimental nephrology
BACKGROUND: Chronic kidney disease (CKD) represents a significant public health challenge, with rates consistently on the rise. Enhancing kidney function prediction could contribute to the early detection, prevention, and management of CKD in clinica...

A machine learning-based analysis for the effectiveness of online teaching and learning in Pakistan during COVID-19 lockdown.

Work (Reading, Mass.)
BackgroundThe COVID-19 pandemic has significantly disrupted daily life and education, prompting institutions to adopt online teaching.ObjectiveThis study delves into the effectiveness of these methods during the lockdown in Pakistan, employing machin...

Multistage deep learning for classification of Helicobacter pylori infection status using endoscopic images.

Journal of gastroenterology
BACKGROUND: The automated classification of Helicobacter pylori infection status is gaining attention, distinguishing among uninfected (no history of H. pylori infection), current infection, and post-eradication. However, this classification has rela...

Evaluating a clinically available artificial intelligence model for intracranial aneurysm detection: a multi-reader study and algorithmic audit.

Neuroradiology
PURPOSE: We aimed to validate a clinically available artificial intelligence (AI) model to assist general radiologists in the detection of intracranial aneurysm (IA) in a multi-reader multi-case (MRMC) study, and to explore its performance in routine...

Predicting the risk of a high proportion of three/multiple pronuclei (3PN/MPN) zygotes in individual IVF cycles using comparative machine learning algorithms.

European journal of obstetrics, gynecology, and reproductive biology
BACKGROUND: The majority of machine learning applications in assisted reproduction have been focused on predicting the likelihood of pregnancy. In the present study, we aim to investigate which machine learning models are most effective in predicting...

A comprehensive scoping review on machine learning-based fetal echocardiography analysis.

Computers in biology and medicine
Fetal echocardiography (ultrasound of the fetal heart) plays a vital role in identifying heart defects, allowing clinicians to establish prenatal and postnatal management plans. Machine learning-based methods are emerging to support the automation of...