Hospital-Based Medicine

Intensivists

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

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Showing 988-1008 of 6,152 articles
Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study.

Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion. In this st...

Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights.

The growing concern of pediatric mortality demands heightened preparedness in clinical settings, esp...

A novel plant type, leaf disease and severity identification framework using CNN and transformer with multi-label method.

The growth of plants is threatened by numerous diseases. Accurate and timely identification of these...

DMA-HPCNet: Dual Multi-Level Attention Hybrid Pyramid Convolution Neural Network for Alzheimer's Disease Classification.

Computer-aided diagnosis (CAD) plays a crucial role in the clinical application of Alzheimer's disea...

SAMCF: Adaptive global style alignment and multi-color spaces fusion for joint optic cup and disc segmentation.

The optic cup (OC) and optic disc (OD) are two critical structures in retinal fundus images, and the...

Smart Biosensor for Breast Cancer Survival Prediction Based on Multi-View Multi-Way Graph Learning.

Biosensors play a crucial role in detecting cancer signals by orchestrating a series of intricate bi...

Enhancing aspect-based multi-labeling with ensemble learning for ethical logistics.

In the dynamic domain of logistics, effective communication is essential for streamlined operations....

Active Dynamic Weighting for multi-domain adaptation.

Multi-source unsupervised domain adaptation aims to transfer knowledge from multiple labeled source ...

A robust multi-scale feature extraction framework with dual memory module for multivariate time series anomaly detection.

Although existing reconstruction-based multivariate time series anomaly detection (MTSAD) methods ha...

An interpretable machine learning model for predicting 28-day mortality in patients with sepsis-associated liver injury.

Sepsis-Associated Liver Injury (SALI) is an independent risk factor for death from sepsis. The aim o...

AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes.

Type 2 diabetes (T2D) presents a formidable global health challenge, highlighted by its escalating p...

MFMSNet: A Multi-frequency and Multi-scale Interactive CNN-Transformer Hybrid Network for breast ultrasound image segmentation.

Breast tumor segmentation in ultrasound images is fundamental for quantitative analysis and plays a ...

AVBAE-MODFR: A novel deep learning framework of embedding and feature selection on multi-omics data for pan-cancer classification.

Integration analysis of cancer multi-omics data for pan-cancer classification has the potential for ...

Multi-class boosting for the analysis of multiple incomplete views on microbiome data.

BACKGROUND: Microbiome dysbiosis has recently been associated with different diseases and disorders....

Multi-scale 3D-CRU for EEG emotion recognition.

In this paper, we propose a novel multi-scale 3D-CRU model, with the goal of extracting more discrim...

Evaluating modern intrusion detection methods in the face of Gen V multi-vector attacks with fuzzy AHP-TOPSIS.

The persistent evolution of cyber threats has given rise to Gen V Multi-Vector Attacks, complex and ...

Developing machine learning models to predict multi-class functional outcomes and death three months after stroke in Sweden.

Globally, stroke is the third-leading cause of mortality and disability combined, and one of the cos...

Hybrid deep learning assisted multi classification: Grading of malignant thyroid nodules.

Thyroid nodules are commonly diagnosed with ultrasonography, which includes internal characteristics...

Concept Recognition and Characterization of Patients Undergoing Resection of Vestibular Schwannoma Using Natural Language Processing.

 Natural language processing (NLP), a subset of artificial intelligence (AI), aims to decipher unst...

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