Critical Care

Improving Intensive Care Unit Early Readmission Prediction Using Optimized and Explainable Machine Learning.

It is of great interest to develop and introduce new techniques to automatically and efficiently ana...

Monitoring the respiratory behavior of multiple cows based on computer vision and deep learning.

Automatic respiration monitoring of dairy cows in modern farming not only helps to reduce manual lab...

LGEANet: LSTM-global temporal convolution-external attention network for respiratory motion prediction.

PURPOSE: To develop a deep learning network that treats the three-dimensional respiratory motion sig...

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early...

Logistic regression technique is comparable to complex machine learning algorithms in predicting cognitive impairment related to post intensive care syndrome.

To evaluate the performance of machine learning (ML) models and to compare it with logistic regressi...

Conventional Versus Artificial Intelligence-Assisted Interpretation of Chest Radiographs in Patients With Acute Respiratory Symptoms in Emergency Department: A Pragmatic Randomized Clinical Trial.

OBJECTIVE: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can...

Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases.

Chronic obstructive pulmonary disease (COPD) concerns the serious decline of human lung functions. T...

Artificial Intelligence and Machine Learning in Dialysis: Ready for Prime Time?

Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population.

In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or...

Image augmentation and automated measurement of endotracheal-tube-to-carina distance on chest radiographs in intensive care unit using a deep learning model with external validation.

BACKGROUND: Chest radiographs are routinely performed in intensive care unit (ICU) to confirm the co...

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...

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...

Knowledge Graph Embeddings for ICU readmission prediction.

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

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 ...

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...

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 ...

Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population.

This study aimed to assess the image quality and accuracy of respiratory-gated real-time two-dimensi...

FedSepsis: A Federated Multi-Modal Deep Learning-Based Internet of Medical Things Application for Early Detection of Sepsis from Electronic Health Records Using Raspberry Pi and Jetson Nano Devices.

The concept of the Internet of Medical Things brings a promising option to utilize various electroni...

Machine Learning Models for the Automatic Detection of Exercise Thresholds in Cardiopulmonary Exercising Tests: From Regression to Generation to Explanation.

The cardiopulmonary exercise test (CPET) constitutes a gold standard for the assessment of an indivi...

Compensation for respiratory motion-induced signal loss and phase corruption in free-breathing self-navigated cine DENSE using deep learning.

PURPOSE: To introduce a model that describes the effects of rigid translation due to respiratory mot...