Critical Care

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

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Integrated multi-omics analysis of ovarian cancer using variational autoencoders.

Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., D...

Socially Assistive Robots in Aged Care: Ethical Orientations Beyond the Care-Romantic and Technology-Deterministic Gaze.

Socially Assistive Robots (SARs) are increasingly conceived as applicable tools to be used in aged c...

Research on multi-path dense networks for MRI spinal segmentation.

Accurate and robust segmentation of anatomical structures from magnetic resonance images is valuable...

Multi-source Seq2seq guided by knowledge for Chinese healthcare consultation.

Online healthcare consultation offers people a convenient way to consult doctors. In this paper, we ...

Generalized and transferable patient language representation for phenotyping with limited data.

The paradigm of representation learning through transfer learning has the potential to greatly enhan...

The effect of diabetes on major robotic hepatectomy.

Studies regarding the influence of diabetes on perioperative outcomes after major hepatectomy are co...

A Real-Time Artificial Intelligence-Assisted System to Predict Weaning from Ventilator Immediately after Lung Resection Surgery.

Assessment of risk before lung resection surgery can provide anesthesiologists with information abou...

Automatic deep learning-based pleural effusion classification in lung ultrasound images for respiratory pathology diagnosis.

Lung ultrasound (LUS) imaging as a point-of-care diagnostic tool for lung pathologies has been prove...

Dual self-paced multi-view clustering.

By utilizing the complementary information from multiple views, multi-view clustering (MVC) algorith...

Individualized prediction of COVID-19 adverse outcomes with MLHO.

The COVID-19 pandemic has devastated the world with health and economic wreckage. Precise estimates ...

MAMA Net: Multi-Scale Attention Memory Autoencoder Network for Anomaly Detection.

Anomaly detection refers to the identification of cases that do not conform to the expected pattern,...

Prediction of Sepsis in COVID-19 Using Laboratory Indicators.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health co...

A message-passing multi-task architecture for the implicit event and polarity detection.

Implicit sentiment analysis is a challenging task because the sentiment of a text is expressed in a ...

An effective SteinGLM initialization scheme for training multi-layer feedforward sigmoidal neural networks.

Network initialization is the first and critical step for training neural networks. In this paper, w...

CTNN: A Convolutional Tensor-Train Neural Network for Multi-Task Brainprint Recognition.

Brainprint is a new type of biometric in the form of EEG, directly linking to intrinsic identity. Cu...

R-JaunLab: Automatic Multi-Class Recognition of Jaundice on Photos of Subjects with Region Annotation Networks.

Jaundice occurs as a symptom of various diseases, such as hepatitis, the liver cancer, gallbladder o...

Machine learning based predictors for COVID-19 disease severity.

Predictors of the need for intensive care and mechanical ventilation can help healthcare systems in ...

Multi-Path and Group-Loss-Based Network for Speech Emotion Recognition in Multi-Domain Datasets.

Speech emotion recognition (SER) is a natural method of recognizing individual emotions in everyday ...

Are We Ready for Video Recognition and Computer Vision in the Intensive Care Unit? A Survey.

OBJECTIVE: Video recording and video recognition (VR) with computer vision have become widely used i...

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