Critical Care

Integrated Learning Model-Based Assessment of Enteral Nutrition Support in Neurosurgical Intensive Care Patients.

To observe the clinical efficacy of early enteral nutrition application in critically ill neurosurgi...

A meta-learning algorithm for respiratory flow prediction from FBG-based wearables in unrestrained conditions.

The continuous monitoring of an individual's breathing can be an instrument for the assessment and e...

Multi-task convolutional neural networks for predicting in vitro clearance endpoints from molecular images.

Optimization of compound metabolic stability is a highly topical issue in pharmaceutical research. A...

Development of a deep learning model that predicts Bi-level positive airway pressure failure.

Delaying intubation for patients failing Bi-Level Positive Airway Pressure (BIPAP) may be associated...

Deep Multi-Scale Residual Connected Neural Network Model for Intelligent Athlete Balance Control Ability Evaluation.

Athlete balance control ability plays an important role in different types of sports. Accurate and e...

Prediction of the position of external markers using a recurrent neural network trained with unbiased online recurrent optimization for safe lung cancer radiotherapy.

BACKGROUND AND OBJECTIVE: During lung cancer radiotherapy, the position of infrared reflective objec...

An Analysis of New Feature Extraction Methods Based on Machine Learning Methods for Classification Radiological Images.

The lungs are COVID-19's most important focus, as it induces inflammatory changes in the lungs that ...

Construction and Application of Text Entity Relation Joint Extraction Model Based on Multi-Head Attention Neural Network.

Entity relationship extraction is one of the key areas of information extraction and is an important...

Confusion regarding the use of Natural Language Processing in ICU delirium assessment. Author's reply.

Birdsong classification based on ensemble multi-scale convolutional neural network.

With the intensification of ecosystem damage, birds have become the symbolic species of the ecosyste...

Research on Intelligent Scheduling Scheme of Aerobics Competition for Multi-Intelligent Decision-Making.

Multi-intelligent decision-making has a good development at present. Based on a series of technologi...

AD-CovNet: An exploratory analysis using a hybrid deep learning model to handle data imbalance, predict fatality, and risk factors in Alzheimer's patients with COVID-19.

Alzheimer's disease (AD) is the leading cause of dementia globally, with a growing morbidity burden ...

Multi-Signal Detection Framework: A Deep Learning Based Carrier Frequency and Bandwidth Estimation.

Multi-signal detection is of great significance in civil and military fields, such as cognitive radi...

Soft Multi-Directional Force Sensor for Underwater Robotic Application.

Tactile information is crucial for recognizing physical interactions, manipulation of an object, and...

Leveraging clinical data across healthcare institutions for continual learning of predictive risk models.

The inherent flexibility of machine learning-based clinical predictive models to learn from episodes...

Meta multi-task nuclei segmentation with fewer training samples.

Cells/nuclei deliver massive information of microenvironment. An automatic nuclei segmentation appro...

A deep learning method for translating 3DCT to SPECT ventilation imaging: First comparison with Kr-gas SPECT ventilation imaging.

PURPOSE: This study aimed to evaluate the accuracy of deep learning (DL)-based computed tomography (...

A Deep-Learning-Assisted On-Mask Sensor Network for Adaptive Respiratory Monitoring.

Wearable respiratory monitoring is a fast, non-invasive, and convenient approach to provide early re...

Confusion regarding the use of Natural Language Processing in ICU delirium assessment.

Deep learning-based framework for motion-compensated image fusion in catheterization procedures.

OBJECTIVE: Augmenting X-ray (XR) fluoroscopy with 3D anatomic overlays is an essential technique to ...

Multi-LiDAR Mapping for Scene Segmentation in Indoor Environments for Mobile Robots.

Nowadays, most mobile robot applications use two-dimensional LiDAR for indoor mapping, navigation, a...