Critical Care

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

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A Structure-Aware Hierarchical Graph-Based Multiple Instance Learning Framework for pT Staging in Histopathological Image.

Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to sur...

Multi-level perception fusion dehazing network.

Image dehazing models are critical in improving the recognition and classification capabilities of i...

Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning.

Multi-class cell segmentation in high-resolution Giga-pixel whole slide images (WSI) is critical for...

Multi-omics integration strategy in the post-mortem interval of forensic science.

Estimates of post-mortem interval (PMI), which often serve as pivotal evidence in forensic contexts,...

Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach.

A large share of traffic accidents is related to driver fatigue. In recent years, many studies have ...

Deep learning-based lung sound analysis for intelligent stethoscope.

Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional steth...

Point-wise spatial network for identifying carcinoma at the upper digestive and respiratory tract.

PROBLEM: Artificial intelligence has been widely investigated for diagnosis and treatment strategy d...

MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation.

This work presents the Multi-Bees-Tracker (MBT3D) algorithm, a Python framework implementing a deep ...

SelANet: decision-assisting selective sleep apnea detection based on confidence score.

BACKGROUND: One of the most common sleep disorders is sleep apnea syndrome. To diagnose sleep apnea ...

Autonomous medical needle steering in vivo.

The use of needles to access sites within organs is fundamental to many interventional medical proce...

Fully Integrated Patch Based on Lamellar Porous Film Assisted GaN Optopairs for Wireless Intelligent Respiratory Monitoring.

Respiratory pattern is one of the most crucial indicators for accessing human health, but there has ...

Muffin: A Framework Toward Multi-Dimension AI Fairness by Uniting Off-the-Shelf Models.

Model fairness (a.k.a., bias) has become one of the most critical problems in a wide range of AI app...

An interpretable deep learning model for time-series electronic health records: Case study of delirium prediction in critical care.

Deep Learning (DL) models have received increasing attention in the clinical setting, particularly i...

Artificial Intelligence for Assessment of Endotracheal Tube Position on Chest Radiographs: Validation in Patients From Two Institutions.

Timely and accurate interpretation of chest radiographs obtained to evaluate endotracheal tube (ETT...

Joint learning of feature and topology for multi-view graph convolutional network.

Graph convolutional network has been extensively employed in semi-supervised classification tasks. A...

OHO: A Multi-Modal, Multi-Purpose Dataset for Human-Robot Object Hand-Over.

In the context of collaborative robotics, handing over hand-held objects to a robot is a safety-crit...

COVID-19 diagnosis using clinical markers and multiple explainable artificial intelligence approaches: A case study from Ecuador.

The COVID-19 pandemic erupted at the beginning of 2020 and proved fatal, causing many casualties wor...

Causal multi-label learning for image classification.

In this paper, we investigate the problem of causal image classification with multi-label learning. ...

A multi-tier deterioration assessment models for sewer and stormwater pipelines in Hong Kong.

Sewerage and stormwater networks are subjected to several deterioration factors, including aging, en...

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