Sepsis

Development and validation of an interpretable machine learning model for predicting in-hospital mortality among critically ill patients with liver cirrhosis.

This study aimed to develop and validate an interpretable machine learning model for early prediction of in-hospital mortality in critically ill patients with liver cirrhosis to optimize risk stratification and individualized clinical intervention. A total of 5358 cirrhotic ICU patients were retrospectively selected from the MIMIC-IV database and randomly divided into training and internal validat...

Using interpretable machine learning to analyze the trajectory changes of serum albumin to predict the mortality rate of sepsis: a cohort study based on MIMIC-IV.

BACKGROUND: Although hypoalbuminemia at ICU admission is associated with increased in-hospital mortality in septic patients, the prognostic value of serum albumin trajectory changes based on repeated measurements remains unclear. This study aimed to identify longitudinal serum albumin trajectory changes, evaluate their association with clinical outcomes at different temporal windows, and construct...

Detection of malaria infection from parasite-free blood smears.

Malaria affects almost 263 million people worldwide, most of whom live in sub-Saharan countries. In a strategy to reduce malaria-related mortality and...

Identification of lactate metabolism-related genes as kidney fibrosis biomarkers through integrated transcriptomic and experimental analyses.

Kidney fibrosis, the final pathological outcome of chronic kidney disease, lacks reliable biomarkers, and the role of lactylation in its pathogenesis ...

Development and validation of a routine blood test-based model to predict in-hospital postoperative pulmonary infection in older patients with hip fracture.

BACKGROUND: Postoperative pulmonary infection (PPI) is a common and serious complication in older adults undergoing hip fracture surgery, leading to p...

Establishment of a Multimodal Prognostic Prediction Model for Multiple Myeloma Patients Based on Radiomics and Clinical Features: A Retrospective Cohort Study.

OBJECTIVE: We aimed to develop a survival prediction system integrating radiomics and clinical features for newly diagnosed multiple myeloma (MM), and...

α-Synuclein Seeds Amplification Assays for Parkinson's Disease and Related Synucleinopathies.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the pathological misfolding and aggregation of α-synuclein (α-sy...

Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.

This study aimed to develop and validate an interpretable machine learning (ML) model using routine laboratory data to support clinical decision-makin...

Machine Learning-Augmented Traditional Analysis of Lactate vs Lactate-to-Albumin Ratio for Predicting Mortality Risk in Patients With Sepsis: Large-Scale Retrospective Study.

BACKGROUND: Effective risk stratification in sepsis remains a critical clinical challenge. Serum lactate is a cornerstone biomarker of metabolic dysfu...

Physics-Informed LSTM Neural Network for Personalized Pharmacokinetic Modeling of Polymyxin B in Critically Ill Patients.

Polymyxin B represents a critical last-resort antibiotic for carbapenem-resistant Gram-negative infections, yet its narrow therapeutic window and subs...

Prognostic survival models for diffuse large B-cell lymphoma using statistical and machine learning approaches.

Although diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, existing prognostic tools, including the revised International Prognostic I...

Acute kidney injury severity in ICU patients: Developing and evaluating a data-driven analysis of clinical covariates using machine learning.

BACKGROUND: Acute kidney injury remains a major cause of morbidity and mortality in critically ill patients. Existing classification systems rely on s...

Integrated multi-omics and machine learning identify OGDHL as a key regulator of glioblastoma progression and antitumor immunity via glutamine metabolism and histone lactylation.

BACKGROUND: Glioblastoma (GBM) has an extremely poor prognosis, and its malignant progression is closely associated with glutamine metabolic reprogram...

Machine Learning-Based Early Risk Stratification for Sepsis-Related Troponin-Defined Myocardial Injury Using Routine Metabolic Indicators.

BACKGROUND: Early recognition of sepsis-related myocardial injury during sepsis remains difficult, partly because harmonized echocardiographic phenoty...

Construction and validation of a phenotypic prediction model for bacterial gentamicin resistance using deep learning with gene sequences.

The emergence of bacterial resistance to antibiotics poses a significant threat to human health; thus, there is an urgent need for new strategies in u...

Rapid diagnostics innovations for urinary tract infections using molecular biology, artificial intelligence and antimicrobial resistance surveillance: a comprehensive review.

Urinary tract infections (UTIs) are among the most prevalent bacterial infections worldwide, accounting for a major clinical impact due to high recurr...

Leashing heterogeneous sepsis with phenotype-informed decision support modeling.

Research progress on detection technologies for Mycoplasma pneumoniae.

Mycoplasma pneumoniae (M. pneumoniae) is a primary pathogen responsible for community-acquired pneumonia (CAP), particularly prevalent among children ...

Ketogenic β-hydroxybutyrate-regulated β-hydroxybutyrylation of HSPE1 alleviates neuronal apoptosis in MPTP/MPP+ induced Parkinson's disease models.

Lysine β-hydroxybutyrylation (Kbhb) is an emerging post-translational modification regulated by β-hydroxybutyrate (BHB), a key metabolic intermediate ...

A pH-Calibrated Multi-Analyte MXene Aerogel Electrochemical Platform Assisted by Interpretable Machine Learning for CSF-Based Prescreening of Postoperative Bacterial Meningitis.

Rapid and reliable prescreening and early risk stratification of postoperative meningitis (PNM) remain challenging because clinical symptoms are nonsp...