Critical Care

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

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Showing 1597-1617 of 7,427 articles
Machine learning and multi-omics data in chronic lymphocytic leukemia: the future of precision medicine?

Chronic lymphocytic leukemia is a complex and heterogeneous hematological malignancy. The advance of...

LPI-SKMSC: Predicting LncRNA-Protein Interactions with Segmented k-mer Frequencies and Multi-space Clustering.

 Long noncoding RNAs (lncRNAs) have significant regulatory roles in gene expression. Interactions wi...

Antioxidant, enzymes inhibitory, physicochemical and sensory properties of instant bio-yoghurts containing multi-purpose natural additives.

This study aimed to assess the antioxidant, enzyme inhibitory, physicochemical and sensory propertie...

Multi-model genome-wide association studies for appearance quality in rice.

Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putati...

Federated clustered multi-domain learning for health monitoring.

Wearable Internet of Things (WIoT) and Artificial Intelligence (AI) are rapidly emerging technologie...

Measuring Implicit Bias in ICU Notes Using Word-Embedding Neural Network Models.

BACKGROUND: Language in nonmedical data sets is known to transmit human-like biases when used in nat...

Contrastive and adversarial regularized multi-level representation learning for incomplete multi-view clustering.

Incomplete multi-view clustering is a significant task in machine learning, given that complex syste...

[Potential of AI for the Treatment of Acute Respiratory Distress Syndrome (ARDS)].

Acute respiratory distress syndrome (ARDS) is still associated with high mortality rates and poses a...

EMAT: Efficient feature fusion network for visual tracking via optimized multi-head attention.

The tracking methods based on Transformer have shown great potential in visual tracking and achieved...

DeBERTa-BiLSTM: A multi-label classification model of Arabic medical questions using pre-trained models and deep learning.

It is wise to investigate past and present epidemics in the hopes of profiting from them and being b...

The clinical course of hospitalized COVID-19 patients and aggravation risk prediction models: a retrospective, multi-center Korean cohort study.

BACKGROUND: Understanding the clinical course and pivotal time points of COVID-19 aggravation is cri...

Heart rate complexity helps mortality prediction in the intensive care unit: A pilot study using artificial intelligence.

BACKGROUND: In intensive care units (ICUs), accurate mortality prediction is crucial for effective p...

Deep learning-based prediction of in-hospital mortality for sepsis.

As a serious blood infection disease, sepsis is characterized by a high mortality risk and many comp...

Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis.

BACKGROUND: The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the...

Multi-pose-based convolutional neural network model for diagnosis of patients with central lumbar spinal stenosis.

Although the role of plain radiographs in diagnosing lumbar spinal stenosis (LSS) has declined in im...

Potential diagnostic application of a novel deep learning- based approach for COVID-19.

COVID-19 is a highly communicable respiratory illness caused by the novel coronavirus SARS-CoV-2, wh...

GATR-3, a Peptide That Eradicates Preformed Biofilms of Multidrug-Resistant .

is a gram-negative bacterium that causes hospital-acquired and opportunistic infections, resulting ...

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