Hospital-Based Medicine

Intensivists

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

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A Multi-Group Multi-Stream attribute Attention network for fine-grained zero-shot learning.

Fine-grained visual categorization in zero-shot setting is a challenging problem in the computer vis...

Interpretable medical image Visual Question Answering via multi-modal relationship graph learning.

Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language M...

Retrospective analysis of interpretable machine learning in predicting ICU thrombocytopenia in geriatric ICU patients.

We developed an interpretable machine learning algorithm that prospectively predicts the risk of thr...

Pre-gating and contextual attention gate - A new fusion method for multi-modal data tasks.

Multi-modal representation learning has received significant attention across diverse research domai...

A novel optimization-assisted multi-scale and dilated adaptive hybrid deep learning network with feature fusion for event detection from social media.

Social media networks become an active communication medium for connecting people and delivering new...

Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution.

Traffic flow prediction is crucial for efficient traffic management. It involves predicting vehicle ...

A two-stage importance-aware subgraph convolutional network based on multi-source sensors for cross-domain fault diagnosis.

Graph convolutional networks (GCNs) as the emerging neural networks have shown great success in Prog...

CBG-Net: Cross-modality and cross-scale balance network with global semantics for multi-modal 3D object detection.

Multi-modal 3D object detection is instrumental in identifying and localizing objects within 3D spac...

Multi-degradation-adaptation network for fundus image enhancement with degradation representation learning.

Fundus image quality serves a crucial asset for medical diagnosis and applications. However, such im...

A weighted prior tensor train decomposition method for community detection in multi-layer networks.

Community detection in multi-layer networks stands as a prominent subject within network analysis re...

Multi-omics based artificial intelligence for cancer research.

With significant advancements of next generation sequencing technologies, large amounts of multi-omi...

Broad learning system based on maximum multi-kernel correntropy criterion.

The broad learning system (BLS) is an effective machine learning model that exhibits excellent featu...

Multi-Task ADME/PK prediction at industrial scale: leveraging large and diverse experimental datasets.

ADME (Absorption, Distribution, Metabolism, Excretion) properties are key parameters to judge whethe...

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