Intensivists

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...

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing...

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

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...

Fungal secondary metabolites in food and pharmaceuticals in the era of multi-omics.

Fungi produce several bioactive metabolites, pigments, dyes, antioxidants, polysaccharides, and indu...

Multi-Sensor Fusion by CWT-PARAFAC-IPSO-SVM for Intelligent Mechanical Fault Diagnosis.

A new method of multi-sensor signal analysis for fault diagnosis of centrifugal pump based on parall...

Beyond technology: Can artificial intelligence support clinical decisions in the prediction of sepsis?

OBJECTIVE: To analyze the critical alarms predictors of clinical deterioration/sepsis for clinical d...

SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.

BACKGROUND: The high volume of research focusing on extracting patient information from electronic h...

Multi-input adaptive neural network for automatic detection of cervical vertebral landmarks on X-rays.

Cervical vertebral landmark detection is a significant pre-task for vertebral relative motion parame...

Investigating a Dual-Channel Network in a Sustainable Closed-Loop Supply Chain Considering Energy Sources and Consumption Tax.

This paper proposes a dual-channel network of a sustainable Closed-Loop Supply Chain (CLSC) for rice...

Fusing pre-trained convolutional neural networks features for multi-differentiated subtypes of liver cancer on histopathological images.

Liver cancer is a malignant tumor with high morbidity and mortality, which has a tremendous negative...

Challenging molecular dogmas in human sepsis using mathematical reasoning.

Sepsis is defined as a dysregulated host-response to infection, across all ages and pathogens. What ...

Multi-state MRAM cells for hardware neuromorphic computing.

Magnetic tunnel junctions (MTJ) have been successfully applied in various sensing application and di...

MHA-CoroCapsule: Multi-Head Attention Routing-Based Capsule Network for COVID-19 Chest X-Ray Image Classification.

The outbreak of COVID-19 threatens the lives and property safety of countless people and brings a tr...

Multi-Output Selective Ensemble Identification of Nonlinear and Nonstationary Industrial Processes.

A key characteristic of biological systems is the ability to update the memory by learning new knowl...

POTTER-ICU: An artificial intelligence smartphone-accessible tool to predict the need for intensive care after emergency surgery.

BACKGROUND: Delays in admitting high-risk emergency surgery patients to the intensive care unit resu...

MR-FPN: Multi-Level Residual Feature Pyramid Text Detection Network Based on Self-Attention Environment.

With humanity entering the age of intelligence, text detection technology has been gradually applied...

Attention-modulated multi-branch convolutional neural networks for neonatal brain tissue segmentation.

Accurate measurement of brain structures is essential for the evaluation of neonatal brain growth an...

Task-State EEG Signal Classification for Spatial Cognitive Evaluation Based on Multiscale High-Density Convolutional Neural Network.

In this study, a multi-scale high-density convolutional neural network (MHCNN) classification method...