Critical Care

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

7,427 articles
Stay Ahead - Weekly Critical Care research updates
Subscribe
Browse Specialties
Subcategories: Sepsis
Showing 946-966 of 7,427 articles
Enhancing suicidal behavior detection in EHRs: A multi-label NLP framework with transformer models and semantic retrieval-based annotation.

BACKGROUND: Suicide is a leading cause of death worldwide, making early identification of suicidal b...

Multi-Label Chest X-Ray Image Classification With Single Positive Labels.

Deep learning approaches for multi-label Chest X-ray (CXR) images classification usually require lar...

Accurate Airway Tree Segmentation in CT Scans via Anatomy-Aware Multi-Class Segmentation and Topology-Guided Iterative Learning.

Intrathoracic airway segmentation in computed tomography is a prerequisite for various respiratory d...

MCPL: Multi-Modal Collaborative Prompt Learning for Medical Vision-Language Model.

Multi-modal prompt learning is a high-performance and cost-effective learning paradigm, which learns...

A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI.

In the current era, a lot of research is being done in the domain of disease diagnosis using machine...

A multi-layer perceptron neural network for varied conditional attributes in tabular dispersed data.

The paper introduces a novel approach for constructing a global model utilizing multilayer perceptro...

Multi-Biometric Feature Extraction from Multiple Pose Estimation Algorithms for Cross-View Gait Recognition.

Gait recognition is a behavioral biometric technique that identifies individuals based on their uniq...

Hybrid contrastive multi-scenario learning for multi-task sequential-dependence recommendation.

Multi-scenario and multi-task learning are crucial in industrial recommendation systems to deliver h...

Developing a prediction model for cognitive impairment in older adults following critical illness.

BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an...

Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning.

Integrating diverse types of biological data is essential for a holistic understanding of cancer bio...

Predicting early mortality in hemodialysis patients: a deep learning approach using a nationwide prospective cohort in South Korea.

Early mortality after hemodialysis (HD) initiation significantly impacts the longevity of HD patient...

Multi-hop interpretable meta learning for few-shot temporal knowledge graph completion.

Multi-hop path completion is a key part of temporal knowledge graph completion, which aims to infer ...

Research on Multi-Scale Spatio-Temporal Graph Convolutional Human Behavior Recognition Method Incorporating Multi-Granularity Features.

Aiming at the problem that the existing human skeleton behavior recognition methods are insensitive ...

Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.

Stroke is a neurological complication that can occur in patients admitted to the intensive care unit...

Machine learning-enhanced multi-trait genomic prediction for optimizing cannabinoid profiles in cannabis.

Cannabis sativa L., known for its medicinal and psychoactive properties, has recently experienced ra...

Identification of CCR7 and CBX6 as key biomarkers in abdominal aortic aneurysm: Insights from multi-omics data and machine learning analysis.

Abdominal aortic aneurysm (AAA) is a severe vascular condition, marked by the progressive dilation o...

Unlocking biological complexity: the role of machine learning in integrative multi-omics.

The increasing complexity of biological systems demands advanced analytical approaches to decode the...

Precision Opioid Prescription in ICU Surgery: Insights from an Interpretable Deep Learning Framework.

PURPOSE: Appropriate opioid management is crucial to reduce opioid overdose risk for ICU surgical pa...

Multi-scale region selection network in deep features for full-field mammogram classification.

Early diagnosis and treatment of breast cancer can effectively reduce mortality. Since mammogram is ...

Browse Specialties