Sepsis

Accelerating Leigh syndrome drug discovery through deep learning screening in brain organoids.

Leigh syndrome (Leigh) is an untreatable mitochondrial disorder characterized by lactic acidosis and...

Machine learning predicts ICU mortality in cardiogenic shock: interpreting SOFA, lactate, and pH thresholds.

Distinct signatures in the human gut and oral microbiomes of gastric cancer.

Microbiome dysbiosis is increasingly recognized as a hallmark of gastric cancer (GC). Here, we analy...

Development of a calibrated logistic regression clinical risk score for predicting postoperative sepsis following retrograde intrarenal surgery.

Circulating Neutrophils Exhibit an Altered Immune Response in Chronic LUTS: An Image-Based Deep Learning Analysis.

INTRODUCTION AND HYPOTHESIS: Chronic lower urinary tract symptoms (LUTS) are characterised by persis...

Development of a LightGBM-based survival prediction model for major burn patients using LDH/LYM ratio as the core predictor.

BACKGROUND: Patients with extensive burns face a high mortality risk. Early identification of progno...

Explainable machine learning for predicting infections that require hospitalization in patients with systemic lupus erythematosus.

OBJECTIVES: To develop and validate an explainable artificial intelligence (XAI)-based machine learn...

Realizing Aqueous High-Order Tripartite Synapse.

Future integration of artificial intelligence in biological settings imposes a non-negotiable requir...

Multi-neurotransmitter synergistically regulated basal ganglia reinforcement learning model.

As a core brain region for motor control and cognitive decision-making, the basal ganglia relies on ...

Decoupling lactylation-associated metabolic remodelling in Asthma: Integrated multi-omics and machine learning identify RCC2 as a potential therapeutic target.

BACKGROUND: Aerobic glycolysis promotes lactate accumulation and histone lactylation (Kla), yet the ...

A scale-down mini-bioreactor for the acceleration of data-driven bioprocess optimisation in cell therapy.

Cell therapies have demonstrated great potential for treating a broad range of diseases where conven...

[Comparative observation of analgesic efficacy between liposomal bupivacaine and "cocktail" therapy following artificial intelligence-assisted direct anterior approach total hip arthroplasty: A prospective randomized controlled study].

OBJECTIVE: To compare the analgesic efficacy and safety of liposomal bupivacaine (LB) versus ropivac...

Recent Advances in Lung Transplantation: Innovations Shaping the Next Era.

Lung transplantation (LTx) has undergone rapid advancement over the last 2 decades. Once-limiting ba...

Predicting Postoperative Outcomes in Pediatric Ureteroscopy Using Machine Learning and Explainable AI-EAU Endourology Vision-AI Study.

AIM OF THE STUDY: This study aimed to evaluate the performance of machine learning (ML) algorithms i...

Comparison of AI-based Chatbot Performance in Analyzing Clinical Scenarios versus Medical Residents: A Novel Approach in Chest Diseases Education.

OBJECTIVE: Rapid advancements in artificial intelligence (AI) technologies offer new opportunities i...

Predicting Nosocomial Infections in Hematologic Patients: A Machine Learning Model Based on Dynamic Body Temperature Trajectories.

AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the ear...

Hypotension Prediction Index-Guided Hemodynamic Management on Postoperative Organ Outcome: A Systematic Review and Meta-Analysis of Randomized Clinical Trials.

Intraoperative hypotension (IOH) is a frequent occurrence during noncardiac surgery. Hypotensive epi...

Development of a Predictive Model for the Latency Period in Preterm Premature Rupture of Membranes Before 32 Weeks' Gestation.

BACKGROUND: Only 13.7% of corticosteroid treatments occurred within the most effective treatment tim...

Performance of Machine Learning Models for Sepsis and Stroke Detection Using EMS Data.

OBJECTIVES: Early sepsis and stroke recognition by emergency medical services (EMS) improves triage,...

Explainable machine learning for predicting mechanical ventilation in Alzheimer's patients with pneumonia: a SHAP-guided XGBoost nomogram based on MIMIC-IV.

Alzheimer's disease (AD) patients are particularly vulnerable to pneumonia and subsequent respirator...

Microbiome and multi-omics insights into sustainable aquaculture: A triennial systematic review.

Aquaculture is the fastest-growing food production sector, yet intensive practices drive disease out...