Critical Care

Sepsis

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

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Showing 2821-2840 of 8,827 articles

Individualized multi-treatment response curves estimation using RBF-net with shared neurons.

Heterogeneous treatment effect estimation is an important problem in precision medicine. Specific interests lie in identifying the differential effect of different treatments based on some external covariates. We propose a novel non-parametric treatment effect estimation method in a multi-treatment setting. Our non-parametric modeling of the response curves relies on radial basis function-nets wit...

Jan 7 2025 40037600

Predicting novel pharmacological activities of compounds using PubChem IDs and machine learning (CID-SID ML model)

Significance and Object: The proposed methodology aims to provide time- and cost-effective approach for the early stage in drug discovery. The machine learning models developed in this study used only the identification numbers provided by PubChem. Thus, a drug development researcher who has obtained a PubChem CID and SID can easily identify new functionality of their compound. The approach was ...

Machine Learning-Based Differential Diagnosis of Parkinson's Disease Using Kinematic Feature Extraction and Selection

Parkinson's disease (PD), the second most common neurodegenerative disorder, is characterized by dopaminergic neuron loss and the accumulation of ab...

Nanopore- and AI-empowered microbial viability inference

The ability to differentiate between viable and dead microorganisms in metagenomic data is crucial for various microbial inferences, ranging from asse...

Large Language Model-assisted text mining reveals bacterial pathogen diversity

Compiling and characterising the diversity of bacterial pathogens of humans is a critical challenge to tackle infection risk, especially in the contex...

Neural Timescale of Adolescents Major Depressive Disorder

Adolescent major depressive disorder (MDD) is characterized by heterogeneous symptomatology and complex neurodevelopmental underpinnings. Here, we inv...

SIMPLICITY: an agent-based, multi-scale mathematical model to study SARS-CoV-2 intra- and between-host evolution

Computational tools are frequently used to describe pathogen evolutionary dynamics either within infected hosts or at the population level. However, t...

The Use of DeepQSAR Models for The Discovery of Peptides with Enhanced Antimicrobial and Antibiofilm Potential

Increasing concerns regarding prolonged antibiotic usage have spurred the search for alternative treatments. Antimicrobial peptides (AMPs), first disc...

Molecular unbalances between striosome and matrix compartments characterize the pathogenesis of Huntington’s disease model mouse

The pathogenesis of Huntington’s disease is still incompletely understood, despite the remarkable advances in identifying the molecular effects of the...

Synaptic sign switching mediates online dopamine updates

In the mammalian brain, excitatory and inhibitory synapses are generally distinct and have fixed synaptic signs. Therefore, unlike in artificial neura...

Individual differences in learning and decision-making: the role of COMT Val158Met polymorphism in transitive inference

Understanding the ordinal relationships between items requires constructing a rank order supporting decision-making between options. This process depe...

Functional immune state classification of unlabeled live human monocytes using holotomography and machine learning

Precise evaluation of immune status is critical for managing diseases such as sepsis, in which the immune system transitions between hyper-inflammator...

Mechanistically Informed Machine Learning Links Non-Canonical TCA Cycle Activity to Warburg Metabolism and Hallmarks of Malignancy

Cancer cells undergo extensive metabolic rewiring to support growth, survival, and phenotypic plasticity. A non-canonical variant of the tricarboxylic...

Intra-DNA k-mer Conservation Patterns Encode Evolutionary Selection of Variants

Evolution shapes the structure and content of genomes, yet the contribution of local sequence composition to variant selection remains poorly understo...

A unified derivative-like dopaminergic computation across valences

Dopamine activity in the brain affects decision-making and adaptive behaviors. A wealth of studies indicate that dopamine activity encodes discrepancy...

Transfer learning enables discovery of sub-micromolar antibacterials for ESKAPE pathogens from ultra-large chemical spaces

The rise of antimicrobial resistance, especially among gram-negative ESKAPE pathogens, presents an urgent global health threat. However, the discovery...

Tripleknock: predicting lethal effect of three-gene knockout in bacteria by deep learning

Investigating the lethal effect of multi-gene knockout is essential for discovering novel antibiotics targets and metabolic engineering. Unlike single...

Neurometabolic predictors of mental effort in the frontal cortex

Motivation drives individuals to overcome costs to achieve desired outcomes, such as rewards or avoidance of punishment, with significant variability ...

DeepDiff-SHAP: Interpretable deep learning for subgroup-specific causal inference using conditional SHAP

Precision medicine aims to tailor healthcare strategies to individual differences in genetic, clinical, and environmental factors. However, identifyin...

Non-polio enteroviruses compromise the electrophysiology of a human iPSC-derived neural network

The non-polio enteroviruses enterovirus-D68 (EV-D68) and enterovirus-A71 (EV-A71) are highly prevalent and considered pathogens of increasing health c...

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