Hospital-Based Medicine

Intensivists

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

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Showing 1828-1848 of 6,177 articles
Deep learning assisted multi-omics integration for survival and drug-response prediction in breast cancer.

BACKGROUND: Survival and drug response are two highly emphasized clinical outcomes in cancer researc...

A Novel Graph Neural Network Methodology to Investigate Dihydroorotate Dehydrogenase Inhibitors in Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a particularly aggressive tumor subtype, and dihydroorotate dehydro...

IHG-MA: Inductive heterogeneous graph multi-agent reinforcement learning for multi-intersection traffic signal control.

Multi-agent deep reinforcement learning (MDRL) has been widely applied in multi-intersection traffic...

Review on the photonic techniques suitable for automatic monitoring of the composition of multi-materials wastes in view of their posterior recycling.

In the increasingly pressing context of improving recycling, optical technologies present a broad po...

Effective recognition of human lower limb jump locomotion phases based on multi-sensor information fusion and machine learning.

Jump locomotion is the basic movement of human. However, no thorough research on the recognition of ...

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...

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...

Dual self-paced multi-view clustering.

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

Semi-automated tracking of pain in critical care patients using artificial intelligence: a retrospective observational study.

Monitoring the pain intensity in critically ill patients is crucial because intense pain can cause a...

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 ...

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