Sepsis

Rapid and Differential Diagnosis of Sepsis Stages Using an Advanced 3D Plasmonic Bimetallic Alloy Nanoarchitecture-Based SERS Biosensor Combined with Machine Learning for Multiple Analyte Identification.

Rapid and accurate differential diagnosis of infections, sepsis, and septic shock is essential for preventing unnecessary antibiotic overuse and improving the chance of patient survival. To address this, a 3D gold nanogranule decorated gold-silver alloy nanopillar (AuNG@Au-AgNP) based surface-enhanced Raman scattering (SERS) biosensor is developed, capable of quantitatively profiling immune-relate...

A diagnostic model for sepsis using an integrated machine learning framework approach and its therapeutic drug discovery.

BACKGROUND: Sepsis remains a life-threatening condition in intensive care units (ICU) with high morbidity and mortality rates. Some biomarkers commonly used in clinic do not have the characteristics of rapid and specific growth and rapid decline after effective treatment. Machine learning has shown great potential in early diagnosis, subtype analysis, accurate treatment and prognosis evaluation of...

Artificial intelligence-driven approaches in antibiotic stewardship programs and optimizing prescription practices: A systematic review.

Antimicrobial stewardship programs (ASPs) are essential in optimizing the use of antibiotics to address the global concern of antimicrobial resistance...

Interpretable machine learning-derived nomogram model for early detection of persistent diarrhea in Salmonella typhimurium enteritis: a propensity score matching based case-control study.

BACKGROUND: Salmonella typhimurium infection is a considerable global health concern, particularly in children, where it often leads to persistent dia...

RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS).

Acute respiratory distress syndrome (ARDS) is a severe organ dysfunction associated with significant mortality and morbidity among critically ill pati...

Point-annotation supervision for robust 3D pulmonary infection segmentation by CT-based cascading deep learning.

Infected region segmentation is crucial for pulmonary infection diagnosis, severity assessment, and monitoring treatment progression. High-performance...

MSCMamba: Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module.

Antimicrobial peptides (AMPs) have important developmental prospects as potential candidates for novel antibiotics. Although many studies have been de...

Autoregressive exogenous neural structures for synthetic datasets of olive disease control model with fractional Grünwald-Letnikov solver.

A fundamental element of the Mediterranean diet, olive oil is abundant in heart-healthy monounsaturated fats and antioxidants, lowering the risk of ca...

Machine Learning Assisted-Intelligent Lactic Acid Monitoring in Sweat Supported by a Perspiration-Driven Self-Powered Sensor.

Lactic acid has aroused increasing attention due to its close association with serious diseases. A real-time, dynamic, and intelligent detection metho...

Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides.

Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however, current models face limitations in generating AM...

Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values.

This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to predict systemic inflammatory response syndrome (SIRS...

Neural mechanisms, influencing factors and interventions in empathic pain.

Empathic pain, defined as the emotional resonance with the suffering of others, is akin to the observer's own experience of pain and is vital for buil...

Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.

Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two groups of antidepressants that are the first-line tr...

User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project.

BACKGROUND: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the...

Elucidating the Mechanism of VVTT Infection Through Machine Learning and Transcriptome Analysis.

The vaccinia virus (VV) is extensively utilized as a vaccine vector in the treatment of various infectious diseases, cardiovascular diseases, immunode...

Leveraging machine learning to uncover multi-pathogen infection dynamics across co-distributed frog families.

BACKGROUND: Amphibians are experiencing substantial declines attributed to emerging pathogens. Efforts to understand what drives patterns of pathogen ...

Integrating Machine Learning with MALDI-TOF Mass Spectrometry for Rapid and Accurate Antimicrobial Resistance Detection in Clinical Pathogens.

Antimicrobial resistance (AMR) is one of the most pressing public health challenges of the 21st century. This study aims to evaluate the efficacy of m...

Machine learning-based lactate-related genes signature predicts clinical outcomes and unveils novel therapeutic targets in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC), a predominant subtype of esophageal cancer, typically presents with poor prognosis. Lactate is a crucial me...

Significance of gender, brain region and EEG band complexity analysis for Parkinson's disease classification using recurrence plots and machine learning algorithms.

Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating dopamine in the SN per compacta. Electroencephalogr...

AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study.

BACKGROUND: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Fai...