Critical Care

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

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Showing 568-588 of 7,417 articles
TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification.

Multivariate time series classification (TSC) is critical for various applications in fields such as...

PyGlaucoMetrics: A Stacked Weight-Based Machine Learning Approach for Glaucoma Detection Using Visual Field Data.

: Glaucoma (GL) classification is crucial for early diagnosis and treatment, yet relying solely on s...

Uncovering hidden subtypes in dementia: An unsupervised machine learning approach to dementia diagnosis and personalization of care.

OBJECTIVE: Dementia represents a growing public health challenge, affecting an increasing number of ...

Infusing Multi-Hop Medical Knowledge Into Smaller Language Models for Biomedical Question Answering.

MedQA-USMLE is a challenging biomedical question answering (BQA) task, as its questions typically in...

Weighted Multi-Modal Contrastive Learning Based Hybrid Network for Alzheimer's Disease Diagnosis.

Multiple imaging modalities and specific proteins in the cerebrospinal fluid, providing a comprehens...

The impact of multi-modality fusion and deep learning on adult age estimation based on bone mineral density.

INTRODUCTION: Age estimation, especially in adults, presents substantial challenges in different con...

ActBeCalf: Accelerometer-based multivariate time-series dataset for calf behavior classification.

Getting new insights on pre-weaned calf behavioral adaptation to routine challenges (transport, grou...

Explainable attention-enhanced heuristic paradigm for multi-view prognostic risk score development in hepatocellular carcinoma.

PURPOSE: Existing prognostic staging systems depend on expensive manual extraction by pathologists, ...

AI Enhanced explainable early prediction of blood culture positivity in neutropenic patients using clinical and hematologic parameters.

Leukemia patients who receive chemotherapy experience a decline in neutrophils and an increased risk...

A MEMS seismometer respiratory monitor for work of breathing assessment and adventitious lung sounds detection via deep learning.

Physicians evaluate a patient's respiratory health during a physical examination by visual assessmen...

Multi-agent large language model frameworks: Unlocking new possibilities for optimizing wastewater treatment operation.

Wastewater treatment plants (WWTPs) are highly complex systems where biological, chemical, and physi...

Semi-Automated Multi-Label Classification of Autistic Mannerisms by Machine Learning on Post Hoc Skeletal Tracking.

Mannerisms describe repetitive or unconventional body movements like arm flapping. These movements a...

Subphenotyping prone position responders with machine learning.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a heterogeneous condition with varying res...

Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion.

Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vi...

Predicting infant brain connectivity with federated multi-trajectory GNNs using scarce data.

The understanding of the convoluted evolution of infant brain networks during the first postnatal ye...

Progressive multi-task learning for fine-grained dental implant classification and segmentation in CBCT image.

With the ongoing advancement of digital technology, oral medicine transitions from traditional diagn...

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