Critical Care

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

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Multimodal Biomedical Image Segmentation using Multi-Dimensional U-Convolutional Neural Network.

Deep learning recently achieved advancement in the segmentation of medical images. In this regard, U...

Neuromonitoring in the ICU - what, how and why?

PURPOSE OF REVIEW: We selectively review emerging noninvasive neuromonitoring techniques and the evi...

MCPNET: Development of an interpretable deep learning model based on multiple conformations of the compound for predicting developmental toxicity.

The development of deep learning models for predicting toxicological endpoints has shown great promi...

Multi-modal deep learning networks for RGB-D pavement waste detection and recognition.

To create a clean living environment, governments around the world have hired a large number of work...

Detection and quantitative analysis of patient-ventilator interactions in ventilated infants by deep learning networks.

BACKGROUND: The study of patient-ventilator interactions (PVI) in mechanically ventilated neonates i...

High-precision retinal blood vessel segmentation based on a multi-stage and dual-channel deep learning network.

The high-precision segmentation of retinal vessels in fundus images is important for the early diagn...

Attention-Based Deep Learning Model for Prediction of Major Adverse Cardiovascular Events in Peritoneal Dialysis Patients.

Major adverse cardiovascular events (MACE) encompass pivotal cardiovascular outcomes such as myocard...

Snippet Policy Network V2: Knee-Guided Neuroevolution for Multi-Lead ECG Early Classification.

Early time series classification predicts the class label of a given time series before it is comple...

Prediction of Drug-Disease Associations Based on Multi-Kernel Deep Learning Method in Heterogeneous Graph Embedding.

Computational drug repositioning can identify potential associations between drugs and diseases. Thi...

Synchronous Mutual Learning Network and Asynchronous Multi-Scale Embedding Network for miRNA-Disease Association Prediction.

MicroRNA (miRNA) serves as a pivotal regulator of numerous cellular processes, and the identificatio...

Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis.

The integration of artificial intelligence (AI) with Digital Twins (DTs) has emerged as a promising ...

GIT-Mol: A multi-modal large language model for molecular science with graph, image, and text.

Large language models have made significant strides in natural language processing, enabling innovat...

Deep learning for real-time multi-class segmentation of artefacts in lung ultrasound.

Lung ultrasound (LUS) has emerged as a safe and cost-effective modality for assessing lung health, p...

A multi-module algorithm for heartbeat classification based on unsupervised learning and adaptive feature transfer.

The scarcity of annotated data is a common issue in the realm of heartbeat classification based on d...

M2AI-CVD: Multi-modal AI approach cardiovascular risk prediction system using fundus images.

Cardiovascular diseases (CVD) represent a significant global health challenge, often remaining undet...

Scalable Multi-Hierarchy Embedded Platform for Neural Population Simulations.

Brain-inspired structured neural circuits are the cornerstones of both computational and perceived i...

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks.

For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially...

Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases.

INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are leading causes of morbidit...

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