Critical Care

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

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Showing 169-189 of 7,402 articles
Deep learning framework for cardiorespiratory disease detection using smartphone IMU sensors.

Respiratory and cardiovascular diseases represent a significant global health burden, underscoring t...

Radiology report generation using automatic keyword adaptation, frequency-based multi-label classification and text-to-text large language models.

BACKGROUND: Radiology reports are essential in medical imaging, providing critical insights for diag...

The emerging role of artificial intelligence in heart failure.

Heart Failure is a prevalent disease with significant impacts on morbidity and mortality. Heart fail...

Integrating MobileNetV3 and SqueezeNet for Multi-class Brain Tumor Classification.

Brain tumors pose a critical health threat requiring timely and accurate classification for effectiv...

A three-tier AI solution for equitable glaucoma diagnosis across China's hierarchical healthcare system.

Artificial intelligence (AI) offers a solution to glaucoma care inequities driven by uneven resource...

Predicting Unplanned Intubations in Rib Fracture Patients: An Interpretable Machine Learning Approach.

BackgroundTraumatic rib fractures can lead to respiratory complications necessitating unplanned intu...

Machine learning for the prediction of urosepsis using electronic health record data.

Urosepsis, a medical condition resulting from the progression of urinary tract infection (UTI), is a...

Smart-Plexer 2.0: Leveraging New Features of Amplification Curves to Enhance the Selection of Multiplex PCR Assays in Multi-Target Identification.

Multiplex PCR plays a critical role in diagnostics by enabling the detection of multiple targets in ...

Unveiling etiology and mortality risks in community-acquired pneumonia: A machine learning approach.

Community-acquired pneumonia (CAP) is associated with high mortality, and accurate diagnosis and ris...

Reconstruction of Heart-related Imaging from Lung Electrical Impedance Tomography Using Semi-Siamese U-Net.

INTRODUCTION: Electrical Impedance Tomography (EIT) is widely used for bedside ventilation monitorin...

Intelligent diagnosis model for chest X-ray images diseases based on convolutional neural network.

To address misdiagnosis caused by feature coupling in multi-label medical image classification, this...

Hybrid Harris hawks-optimized random forest model for detecting multi-element geochemical anomalies related to mineralization.

Reliable recognition of geochemical anomalies linked to ore deposits is one of the most significant ...

Enhancing gas concentration prediction and ventilation efficiency in deep coal mines: a hybrid DL-Koopman and Fuzzy-PID framework.

With the increasing depth of coal mining operations, traditional ventilation systems are becoming in...

DASNet a dual branch multi level attention sheep counting network.

Grassland sheep counting is essential for both animal husbandry and ecological balance. Accurate pop...

Robust Multi-contrast MRI Medical Image Translation via Knowledge Distillation and Adversarial Attack.

Medical image translation is of great value but is very difficult due to the requirement with style ...

A deep learning model for diagnosis of inherited retinal diseases.

To evaluate the performance of a multi-input deep learning (DL) model in detecting two common inheri...

A multi stage deep learning approach for real-time vehicle detection, tracking, and speed measurement in intelligent transportation systems.

In the field of intelligent transportation, accurate vehicle detection, tracking, and re-identificat...

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