Critical Care

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

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Rice disease detection method based on multi-scale dynamic feature fusion.

In order to enhance the accuracy of rice leaf disease detection in complex farmland environments, an...

Interpretable AI-driven multi-objective risk prediction in heart failure patients with thyroid dysfunction.

INTRODUCTION: Heart Failure (HF) complicated by thyroid dysfunction presents a complex clinical chal...

A transformation uncertainty and multi-scale contrastive learning-based semi-supervised segmentation method for oral cavity-derived cancer.

OBJECTIVES: Oral cavity-derived cancer pathological images (OPI) are crucial for diagnosing oral squ...

A lightweight hyperspectral image multi-layer feature fusion classification method based on spatial and channel reconstruction.

Hyperspectral Image (HSI) classification tasks are usually impacted by Convolutional Neural Networks...

Classification of fashion e-commerce products using ResNet-BERT multi-modal deep learning and transfer learning optimization.

As the fashion e-commerce markets rapidly develop, tens of thousands of products are registered dail...

Real estate valuation with multi-source image fusion and enhanced machine learning pipeline.

The automated valuation model (AVM) has been widely used by real estate stakeholders to provide accu...

A criterion for assessing obstacle-induced environmental complexity in multi-robot coverage exploration.

In many applications, such as coverage exploration and search and rescue missions, accurately assess...

Deployable machine learning-based decision support system for tracheostomy in acute burn patients.

BACKGROUND: Airway obstruction is a common emergency in acute burns with high mortality. Tracheostom...

Predicting Superaverage Length of Stay in COPD Patients with Hypercapnic Respiratory Failure Using Machine Learning.

OBJECTIVE: The purpose of this study was to develop and validate machine learning models that can pr...

Reliability of Emotion Analysis from Human Facial Expressions Using Multi-task Cascaded Convolutional Neural Networks.

Life support robots in care settings must be able to read a person's emotions from facial expression...

mGNN-bw: Multi-Scale Graph Neural Network Based on Biased Random Walk Path Aggregation for ASD Diagnosis.

In recent years, computationally assisted diagnosis for classifying autism spectrum disorder (ASD) a...

A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration.

INTRODUCTION: Medical device recalls are important to the practice of emergency medicine, as unsafe ...

A Topology-Enhanced Multi-Viewed Contrastive Approach for Molecular Graph Representation Learning and Classification.

In recent times, graph representation learning has been becoming a hot research topic which has attr...

[Gesture accuracy recognition based on grayscale image of surface electromyogram signal and multi-view convolutional neural network].

This study aims to address the limitations in gesture recognition caused by the susceptibility of te...

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, mak...

A Respiratory Signal Monitoring Method Based on Dual-Pathway Deep Learning Networks in Image-Guided Robotic-Assisted Intervention System.

BACKGROUND: Percutaneous puncture procedures, guided by image-guided robotic-assisted intervention (...

Multi-target neural network model of anxiolytic activity of chemical compounds using correlation convolution of multiple docking energy spectra.

Anxiety disorders are one of the most common mental health pathologies in the world. They require se...

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