Hospital-Based Medicine

Intensivists

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

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SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for Prior-Informed Assessment of Muscle Function and Pathology.

Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as ...

MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data.

Large-scale data obtained from aggregation of already collected multi-site neuroimaging datasets has...

Multi-Camera-Based Human Activity Recognition for Human-Robot Collaboration in Construction.

As the use of construction robots continues to increase, ensuring safety and productivity while work...

Using machine learning to estimate health spillover effects.

We develop a nonparametric model to study health spillover effects of policy interventions. We use d...

Sparse solution of least-squares twin multi-class support vector machine using ℓ and ℓ-norm for classification and feature selection.

In the realm of multi-class classification, the twin K-class support vector classification (Twin-KSV...

Childhood Leukemia Classification via Information Bottleneck Enhanced Hierarchical Multi-Instance Learning.

Leukemia classification relies on a detailed cytomorphological examination of Bone Marrow (BM) smear...

Multi-dimensional deep learning drives efficient discovery of novel neuroprotective peptides from walnut protein isolates.

Neurodegenerative diseases, such as Alzheimer's and Parkinson's, are multi-factor induced neurologic...

ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model.

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) develo...

Recent advances in wearable sensors and data analytics for continuous monitoring and analysis of biomarkers and symptoms related to COVID-19.

The COVID-19 pandemic has changed the lives of many people around the world. Based on the available ...

Safe screening rules for multi-view support vector machines.

Multi-view learning aims to make use of the advantages of different views to complement each other a...

Adaptive Memory of a Neuromorphic Transistor with Multi-Sensory Signal Fusion.

One of the ultimate goals of artificial intelligence is to achieve the capability of memory evolutio...

Lightweight image super-resolution based multi-order gated aggregation network.

Recently, Transformer-based models are taken much focus on solving the task of image super-resolutio...

Multi-institutional PET/CT image segmentation using federated deep transformer learning.

BACKGROUND AND OBJECTIVE: Generalizable and trustworthy deep learning models for PET/CT image segmen...

PhysVENeT: a physiologically-informed deep learning-based framework for the synthesis of 3D hyperpolarized gas MRI ventilation.

Functional lung imaging modalities such as hyperpolarized gas MRI ventilation enable visualization a...

Multidirectional Associative Memory Neural Network Circuit Based on Memristor.

Multidirectional associative memory neural network(MAMNN) is a direct extension of bidirectional ass...

The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.

Artificial Intelligence and Machine learning have been widely used in various fields of mathematical...

Propensity-matched analysis of robotic versus sternotomy approaches for mitral valve replacement.

To compare early and medium-term outcomes between robotic and sternotomy approaches for mitral valve...

Multi-Constraint Latent Representation Learning for Prognosis Analysis Using Multi-Modal Data.

The Cox proportional hazard model has been widely applied to cancer prognosis prediction. Nowadays, ...

Multi-Scale Hybrid Fusion Network for Single Image Deraining.

Deep learning models have been able to generate rain-free images effectively, but the extension of t...

Towards Adversarial Robustness for Multi-Mode Data through Metric Learning.

Adversarial attacks have become one of the most serious security issues in widely used deep neural n...

Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.

Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency D...

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