Hospital-Based Medicine

Intensivists

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

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Neural network-based dynamic target enclosing control for uncertain nonlinear multi-agent systems over signed networks.

Neural networks have significant advantages in the estimation of uncertainty dynamics, which can aff...

3D MFA: An automated 3D Multi-Feature Attention based approach for spine segmentation using a multi-stage network pruning.

Spine segmentation poses significant challenges due to the complex anatomical structure of the spine...

AI-assisted detection for chest X-rays (AID-CXR): a multi-reader multi-case study protocol.

INTRODUCTION: A chest X-ray (CXR) is the most common imaging investigation performed worldwide. Adva...

Local interpretable spammer detection model with multi-head graph channel attention network.

Fraudulent reviews posted by spammers on the online shopping websites mislead consumers' purchasing ...

Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties.

Peptides are crucial in biological processes and therapeutic applications. Given their importance, a...

Enhancing Deep-Learning Classification for Remote Motor Imagery Rehabilitation Using Multi-Subject Transfer Learning in IoT Environment.

One of the most promising applications for electroencephalogram (EEG)-based brain-computer interface...

Accurate Arrhythmia Classification with Multi-Branch, Multi-Head Attention Temporal Convolutional Networks.

Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for...

Predictive modeling of ICU-AW inflammatory factors based on machine learning.

BACKGROUND: ICU-acquired weakness (ICU-AW) is a common complication among ICU patients. We used mach...

SciAgents: Automating Scientific Discovery Through Bioinspired Multi-Agent Intelligent Graph Reasoning.

A key challenge in artificial intelligence (AI) is the creation of systems capable of autonomously a...

A prior-knowledge-guided dynamic attention mechanism to predict nocturnal hypoglycemic events in type 1 diabetes.

Nocturnal hypoglycemia is a critical problem faced by diabetic patients. Failure to intervene in tim...

Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection.

BACKGROUND: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the...

SurgiTrack: Fine-grained multi-class multi-tool tracking in surgical videos.

Accurate tool tracking is essential for the success of computer-assisted intervention. Previous effo...

Machine Learning-Based Prediction Model for ICU Mortality After Continuous Renal Replacement Therapy Initiation in Children.

BACKGROUND: Continuous renal replacement therapy (CRRT) is the favored renal replacement therapy in ...

Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.

Thyroid diseases, including functional and neoplastic diseases, bring a huge burden to people's heal...

Spontaneous Hepatic Rupture Complicating Preeclampsia and HELLP Syndrome: A Case Report.

Spontaneous hepatic rupture is a rare complication that occurs in pregnant mothers with HELLP syndr...

DFASGCNS: A prognostic model for ovarian cancer prediction based on dual fusion channels and stacked graph convolution.

Ovarian cancer is a malignant tumor with different clinicopathological and molecular characteristics...

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