Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Subcategories: Sepsis
Showing 442-462 of 7,420 articles
Host Biomarkers and Antibiotic Tissue Penetration in Sepsis: Insights from Moxifloxacin.

BACKGROUND AND OBJECTIVE: Sepsis-induced pathophysiological changes may lead to pharmacokinetic vari...

[Acute respiratory distress syndrome-quo vadis : Innovative and individualized treatment approaches].

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome characterized by var...

Explainable machine learning algorithm to predict cardiovascular event in patients undergoing peritoneal dialysis.

OBJECTIVE: To compare the performance of predictive models for cardiovascular event (CVE) in patient...

Enhancing medical text classification with GAN-based data augmentation and multi-task learning in BERT.

With the rapid advancement of medical informatics, the accumulation of electronic medical records an...

Machine learning modeling and multi objective optimization of artificial detrusor.

To address the problem of obtaining optimal design parameters for existing artificial detrusors usin...

Fine-tune language models as multi-modal differential equation solvers.

In the growing domain of scientific machine learning, in-context operator learning has shown notable...

Fine extraction of multi-crop planting area based on deep learning with Sentinel- 2 time-series data.

Accurate and timely access to the spatial distribution of crops is crucial for sustainable agricultu...

Development and external validation of a machine learning model to predict bronchopulmonary dysplasia using dynamic factors.

We hypothesized that incorporating postnatal dynamic factors would enhance the prediction accuracy o...

Heuristically enhanced multi-head attention based recurrent neural network for denial of wallet attacks detection on serverless computing environment.

Denial of Wallet (DoW) attacks are a cyber threat designed to utilize and deplete an organization's ...

Lightweight Multi-Stage Aggregation Transformer for robust medical image segmentation.

Capturing rich multi-scale features is essential to address complex variations in medical image segm...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic....

EffiCOVID-net: A highly efficient convolutional neural network for COVID-19 diagnosis using chest X-ray imaging.

The global COVID-19 pandemic has drastically affected daily life, emphasizing the urgent need for ea...

TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data.

It is challenging to identify regulatory transcriptional regulators (TRs), which control gene expres...

Multi-stage network for single image deblurring based on dual-domain window mamba.

Multi-stage methods have been proven effective and widely used in image deblurring research. These m...

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