Critical Care

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

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Evaluations on supervised learning methods in the calibration of seven-hole pressure probes.

Machine learning method has become a popular, convenient and efficient computing tool applied to man...

Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks.

Accurate prediction of postoperative complications can inform shared decisions regarding prognosis, ...

Machine learning using multi-modal data predicts the production of selective laser sintered 3D printed drug products.

Three-dimensional (3D) printing is drastically redefining medicine production, offering digital prec...

Prospective Real-Time Validation of a Lung Ultrasound Deep Learning Model in the ICU.

OBJECTIVES: To evaluate the accuracy of a bedside, real-time deployment of a deep learning (DL) mode...

Two-Step Approach for Occupancy Estimation in Intensive Care Units Based on Bayesian Optimization Techniques.

Due to the high occupational pressure suffered by intensive care units (ICUs), a correct estimation ...

Knowledge Graph Embeddings for ICU readmission prediction.

BACKGROUND: Intensive Care Unit (ICU) readmissions represent both a health risk for patients,with in...

Intra-person multi-task learning method for chronic-disease prediction.

In the medical field, various clinical information has been accumulated to help clinicians provide p...

Deep learning for improving ZTE MRI images in free breathing.

INTRODUCTION: Despite a growing interest in lung MRI, its broader use in a clinical setting remains ...

NVTrans-UNet: Neighborhood vision transformer based U-Net for multi-modal cardiac MR image segmentation.

With the rapid development of artificial intelligence and image processing technology, medical imagi...

MultiScale-CNN-4mCPred: a multi-scale CNN and adaptive embedding-based method for mouse genome DNA N4-methylcytosine prediction.

N4-methylcytosine (4mC) is an important epigenetic mechanism, which regulates many cellular processe...

A comparison of total thoracoscopic versus robotic approach for cardiac myxoma resection: a single-center retrospective study.

Advances in instrumentation and technique have facilitated minimally invasive surgeries for cardiac ...

Combining multi-objective genetic algorithm and neural network dynamically for the complex optimization problems in physics.

Neural network (NN) has been tentatively combined into multi-objective genetic algorithms (MOGAs) to...

DEML: Drug Synergy and Interaction Prediction Using Ensemble-Based Multi-Task Learning.

Synergistic drug combinations have demonstrated effective therapeutic effects in cancer treatment. D...

Histogram of Oriented Gradients meet deep learning: A novel multi-task deep network for 2D surgical image semantic segmentation.

We present our novel deep multi-task learning method for medical image segmentation. Existing multi-...

An end-end deep learning framework for lesion segmentation on multi-contrast MR images-an exploratory study in a rat model of traumatic brain injury.

Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural inj...

Two phases based training method for designing codewords for a set of perceptrons with each perceptron having multi-pulse type activation function.

This paper proposes a two phases-based training method to design the codewords to map the cluster in...

Multi-Robot Task Scheduling with Ant Colony Optimization in Antarctic Environments.

This paper addresses the problem of multi-robot task scheduling in Antarctic environments. There are...

Automated multi-modal Transformer network (AMTNet) for 3D medical images segmentation.

Over the past years, convolutional neural networks based methods have dominated the field of medical...

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