Sepsis

Rapid detection of carbapenem-resistant Escherichia coli and carbapenem-resistant Klebsiella pneumoniae in positive blood cultures via MALDI-TOF MS and tree-based machine learning models.

BACKGROUND: Bloodstream infection (BSI) is a systemic infection that predisposes individuals to sepsis and multiple organ dysfunction syndrome. Early identification of infectious agents and determination of drug-resistant phenotypes can help patients with BSI receive timely, effective, and targeted treatment and improve their survival. This study was based on matrix-assisted laser desorption/ioniz...

Identification of potential biomarkers for 2022 Mpox virus infection: a transcriptomic network analysis and machine learning approach.

Monkeypox virus (MPXV), a zoonotic pathogen, re-emerged in 2022 with the Clade IIb variant, raising global health concerns due to its unprecedented spread in non-endemic regions. Recent studies have shown that Clade IIb (2022 MPXV) is marked by unique genomic mutations and epidemiological behaviors, suggesting variations in host-virus interactions. This study aimed to identify the differentially e...

Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles.

Lung cancer is a devastating public health threat and a leading cause of cancer-related deaths. Therefore, it is imperative to develop sophisticated t...

The clinical prediction model to distinguish between colonization and infection by .

OBJECTIVE: To develop a machine learning-based prediction model to assist clinicians in accurately determining whether the detection of (KP) in sputu...

Leveraging AI-driven nudge theory to enhance hand hygiene compliance: paving the path for future infection control.

Hand hygiene is critical for preventing infections, yet maintaining compliance remains challenging across healthcare, schools, and communities. Despit...

Predicting Postoperative Infection After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy with Splenectomy.

BACKGROUND: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of inf...

Deep learning-based image classification reveals heterogeneous execution of cell death fates during viral infection.

Cell fate decisions, such as proliferation, differentiation, and death, are driven by complex molecular interactions and signaling cascades. While sig...

Machine learning prediction models for mortality risk in sepsis-associated acute kidney injury: evaluating early versus late CRRT initiation.

BACKGROUND: Sepsis-associated acute kidney injury (S-AKI) has a significant impact on patient survival, with continuous renal replacement therapy (CRR...

Developing a rapid screening tool for high-risk ICU patients of sepsis: integrating electronic medical records with machine learning methods for mortality prediction in hospitalized patients-model establishment, internal and external validation, and visualization.

OBJECTIVES: To develop a machine learning-based prediction model using clinical data from the first 24 h of ICU admission to enable rapid screening an...

Comprehensive analysis of causal pathogens and determinants influencing black rot disease development in MD2 pineapples.

Malaysia ranks among the world's top 20 pineapple producers, driven by the success of the MD2 variety in meeting domestic and international demand. Ho...

Predicting work ability impairment in post COVID-19 patients: a machine learning model based on clinical parameters.

The Post COVID-19 condition (PCC) is a complex disease affecting health and everyday functioning. This is well reflected by a patient's inability to w...

Role of Artificial Intelligence in Identifying Vital Biomarkers with Greater Precision in Emergency Departments During Emerging Pandemics.

The COVID-19 pandemic has accelerated advances in molecular biology and virology, enabling the identification of key biomarkers to differentiate betwe...

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

BACKGROUND: The automated classification of Helicobacter pylori infection status is gaining attention, distinguishing among uninfected (no history of ...

A comparative evaluation of antibiotic and synbiotic supplementation on production performance and necrotic enteritis severity in broilers during an experimental necrotic enteritis challenge.

The ban on antibiotics in the poultry diet resulted in re-emergence of several infectious diseases including necrotic enteritis (NE). These infectious...

Molecular detection of in captive black-faced black spider monkeys (mammalia; primate).

The present study aimed to assess spp. infection in 17 captive black-faced black spider monkeys (), living at the Zoological Garden of Curitiba, Para...

E-DFu-Net: An efficient deep convolutional neural network models for Diabetic Foot Ulcer classification.

The Diabetic Foot Ulcer (DFU) is a severe complication that affects approximately 33% of diabetes patients globally, often leading to limb amputation ...

Artificial intelligence performance in ultrasound-based lymph node diagnosis: a systematic review and meta-analysis.

BACKGROUND AND OBJECTIVES: Accurate classification of lymphadenopathy is essential for determining the pathological nature of lymph nodes (LNs), which...

Utilizing artificial intelligence and cellular population data for timely identification of bacteremia in hospitalized patients.

BACKGROUND: Bacteremia is a critical condition with high mortality that requires prompt detection to prevent progression to life-threatening sepsis. T...

deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities.

Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As the problem of pathogen resistance caused by the m...

Combining machine learning and single-cell sequencing to identify key immune genes in sepsis.

This research aimed to identify novel indicators for sepsis by analyzing RNA sequencing data from peripheral blood samples obtained from sepsis patien...