Critical Care

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

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Subcategories: Sepsis
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Dataset-aware multi-task learning approaches for biomedical named entity recognition.

MOTIVATION: Named entity recognition is a critical and fundamental task for biomedical text mining. ...

Revisiting motion-based respiration measurement from videos.

Video-based motion analysis gave rise to contactless respiration rate monitoring that measures subtl...

Evaluation of Machine Learning-based Patient Outcome Prediction Using Patient-specific Difficulty and Discrimination Indices.

Given the extensive use of machine learning in patient outcome prediction, and the understanding tha...

Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach.

Predicting Cardiovascular Length of stay based hospitalization at the time of patients' admitting to...

Practical Machine Learning-Based Sepsis Prediction.

Sepsis is a life-threatening clinical syndrome and one of the most expensive conditions treated in h...

Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal.

Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a ...

The efficacy of support vector machines in modelling deviations from the Beer-Lambert law for optical measurement of lactate.

Lactate is an important biomarker with a significant diagnostic and prognostic ability in relation t...

Deep transfer learning for video-based detection of newborn presence in incubator.

Preterm newborns are prone to late-onset sepsis, leading to a high risk of mortality. Video-based an...

Extracting Membrane Borders in IVUS Images Using a Multi-Scale Feature Aggregated U-Net.

Automatic extraction of the lumen-intima border (LIB) and the media-adventitia border (MAB) in intra...

Malocclusion Classification on 3D Cone-Beam CT Craniofacial Images Using Multi-Channel Deep Learning Models.

Analyzing and interpreting cone-beam computed tomography (CBCT) images is a complicated and often ti...

MDL-IWS: Multi-view Deep Learning with Iterative Watershed for Pulmonary Fissure Segmentation.

Pulmonary fissure segmentation is important for localization of lung lesions which include nodules a...

Robust Deep Learning Framework For Predicting Respiratory Anomalies and Diseases.

This paper presents a robust deep learning framework developed to detect respiratory diseases from r...

Automatic Detection of Respiratory Effort Related Arousals With Deep Neural Networks From Polysomnographic Recordings.

Sleep disorders have become more common due to the modern lifestyle and stress. The most severe case...

A machine learning method for automatic detection and classification of patient-ventilator asynchrony.

Patients suffering from respiratory failure are often put on assisted mechanical ventilation. Patien...

Repurposing factories with robotics in the face of COVID-19.

Can collaborative robots ramp up the production of medical ventilators?

Blood Lactate Concentration Prediction in Critical Care.

Blood lactate concentration is a reliable risk indicator of deterioration in critical care requiring...

Automatic Extraction of Risk Factors for Dialysis Patients from Clinical Notes Using Natural Language Processing Techniques.

Studies have shown that mental health and comorbidities such as dementia, diabetes and cardiovascula...

Conventional Machine Learning and Deep Learning Approach for Multi-Classification of Breast Cancer Histopathology Images-a Comparative Insight.

Automatic multi-classification of breast cancer histopathological images has remained one of the top...

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