Sepsis

Autoshaped choice in artificial neural networks: implications for behavioral economics and neuroeconomics.

An existing neural network model of conditioning was used to simulate autoshaped choice. In this phenomenon, pigeons first receive an autoshaping procedure with two keylight stimuli X and Y separately paired with food in a forward-delay manner, intermittently for X and continuously for Y. Then pigeons receive unreinforced choice test trials of X and Y concurrently present. Most pigeons choose Y. T...

Use of uniform designs in combination with neural networks for viral infection process development.

This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), ...

Robotic voltammetry with carbon nanotube-based sensors: a superb blend for convenient high-quality antimicrobial trace analysis.

A new automated pharmacoanalytical technique for convenient quantification of redox-active antibiotics has been established by combining the benefits ...

Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes.

Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in th...

Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine.

β-Lactam class of antibiotics is used as major therapeutic agent against a number of pathogenic microbes. The widespread and indiscriminate use of ant...

Procalcitonin Strip Test as an Independent Predictor in Acute Pancreatitis.

Plasma procalcitonin (PCT) is a highly specific marker for the diagnosis of bacterial infection and sepsis. Studies have demonstrated its role in the ...

[Infection prevention check-in and infection prevention check-out to prevent nosocomial infections].

BACKGROUND: A precondition for the success of the prevention of SSI is the complete realisation of the proven anti-infective measures in form of the m...

Evaluating GPT-4o Model Proficiency and Clinical Reasoning for Antimicrobial Stewardship in Dentistry

Objectives: Dentists prescribe approximately one in ten antibiotics worldwide, yet antimicrobial stewardship (AMS) remains underemphasized in dental e...

Markerless Motion Capture Reveals Movement Abnormalities in Isolated REM Sleep Behavior Disorder

Objective and scalable approaches for detecting subtle motor impairment in isolated REM sleep behavior disorder (iRBD), a prodromal stage of Parkinson...

Novel Entropy-Based Framework for Quantifying Dynamic Epistemic Uncertainty in Clinical Medicine

The widespread adoption of clinical large language models (LLMs) introduces significant risks of automation bias, premature closure, and clinician des...

Clinical evaluation of artificial intelligence for diagnostics of antibiotic-resistant bacteria

Antimicrobial resistance is a public health challenge, driving the need for rapid, cost-effective diagnostic support tools. Artificial intelligence (A...

Primary Care Quality and Inappropriate Community Antibiotic Use: A Double Machine Learning Instrumental Variable Approach

Inappropriate antibiotic use presents a major global health challenge, particularly in low-resource settings where access to quality care is limited b...

DISRUPTION OF A DNA REPAIR PROTEIN PROMOTES ANTIBIOTIC RESISTANCE IN ACINETOBACTER BAUMANNII

Acinetobacter baumannii is a high priority Gram negative opportunistic pathogen known for its high rates of multidrug resistance (MDR). Minocycline (M...

Learning a Continuous Sepsis Severity Score Without Hour-by-Hour Supervision: A Two-Site Retrospective Study

Currently used sepsis severity indices rely on fixed variables and weights established decades ago, which are coarsely discretized and calibrated to a...

Large Language Model Embeddings of Surgical Procedural Names for Confounding Adjustment in Perioperative Observational Studies

Background: Perioperative observational studies are increasingly used to evaluate anesthesia practices that are difficult to test in randomized trials...

Offline Reinforcement Learning for Out-of-Distribution ICU Sepsis Decision Support

Offline reinforcement learning (RL) provides a promising framework for learning and evaluating treatment policies from logged clinical data, particula...

Dissecting Immune-Epithelial Interactions in Airway Infection at Single-Cell Resolution Using a Compartmentalised Microfluidic Device

Immune-epithelial interactions govern the initiation and progression of airway diseases, yet their heterogeneity is difficult to capture using existin...

Implementation of a clinical decision support tool for acute diarrhea management in Tanzania and the United States: A Qualitative study using the Consolidated Framework for Implementation Research

Background: In two large studies conducted in Bangladesh, our recently developed artificial intelligence (AI)-based models for assessing dehydration s...

Adapting Clinical Event Annotation to Dutch Primary Care: An Event Annotation Framework for Post-Acute Infection Syndromes

Extracting clinical information from Dutch free-text medical notes requires language-specific annotation resources, yet Dutch primary care lacks a reu...

Local retraining mitigates domain shift in sepsis prediction: Lessons from translating a neonatal model to mixed intensive care data

Background: Machine learning models leveraging electronic health records (EHRs) can support earlier detection of sepsis in intensive care units (ICUs)...