Critical Care

Sepsis

Latest AI and machine learning research in sepsis for healthcare professionals.

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Showing 2479-2499 of 7,154 articles
Optimally Predicting Mortality in Patients with Abdominal Aortic Aneurysms

Abdominal aortic aneurysm (AAA) patients in the ICU represent a heterogeneous, high-risk population ...

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A novel dopaminergic critic signal triggered by erroneous strategy choices in mice training in operant tasks

Classically, midbrain dopaminergic neuron activity is triggered by unexpected rewards, then, upon le...

Learning proteomic disease trajectories with flow matching

High-throughput proteomics has enabled detailed characterization of molecular states across health a...

Entropy regularised reinforcement learning reconciles aversive and action prediction errors in the tail of the striatum

Dopamine activity in the tail of the striatum (TS) presents a novel challenge for reinforcement-lear...

The Patients' Voice in Clostridioides difficile Infection: Large Language Model-Assisted Thematic Analysis of Patient Testimonials

Background. Clostridioides difficile infection (CDI) imposes a burden that extends well beyond the g...

Machine learning-based predictive clinical model for Shigella spp. infection in children with diarrhea

Diarrheal disease remains a significant cause of morbidity and mortality in children under five year...

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The Causal Artificial Intelligence Clinician for early haemodynamic management of septic shock in ICU

Introduction: Standardizing fluid and vasopressor resuscitation in sep- tic shock is challenging due...

A five-dimensional functional state space for fingerprinting disease transcriptomes

High-throughput transcriptomics has transformed disease biology, but its outputs often remain fragme...

A systematic analysis of machine learning pipelines for robust antimicrobial resistance prediction

Motivation: Antimicrobial resistance (AMR) has been identified as a top global public health threat....

Reward Valuation in Vision Language Models: Causal Mechanisms Underlying Anhedonia

Recent Vision-Language Models capture increasingly complex aspects of human cognition. Here we ask w...

Improving Generalizability in Whole-Cell Antibiotic Discovery Through Active Learning

Machine learning (ML) has accelerated molecular discovery, yet training models to generalize to out-...

EEG biomarkers of reinforcement learning and motivation: A multi-task battery

Serotonin and dopamine make dissociable contributions to reinforcement learning (RL) sub-components,...

Nutrient-dependent hippocampus dopamine signaling enhances meal-related episodic memory and reduces food intake

Background: Dopamine (DA) is a neurotransmitter critically involved in food-related reinforcement le...

Epigenetic signatures of infection within and across generations in the endangered Loggerhead sea turtle

Infection can substantially reduce host fitness and influence population dynamics, yet it is often d...

Long-range inhibitory control of cholinergic network dynamics in the striatum.

Striatal cholinergic interneurons (CINs) exhibit a transient pause in tonic firing in response to sa...

Proposed Context-of-Use Evaluation Framework for Medication Management Tasks Completed by Generative Artificial Intelligence

Background: Standardized evaluation of agentic artificial intelligence (AI) for medication managemen...

Cross-LLM AI platform meta-research: Non-inferiority of bovine milk-based fortifiers to human milk-based fortifiers

Necrotizing enterocolitis (NEC), frequently resulting in sepsis, is among the leading causes of morb...

Label-free Pathogen Identification with Microscopy Imaging and Deep Learning

Rapid and accurate pathogen identification is crucial for the clinical management of infectious dise...

Real-world results from a Machine Learning-guided, phenotypic High-Throughput Screen for novel antibiotics

Antimicrobial resistance is an urgent global health threat, with over 2.8 million multidrug-resistan...

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