Critical Care

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

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Showing 3739-3759 of 7,482 articles
Pose estimation and tracking dataset for multi-animal behavior analysis on the China Space Station.

Non-contact behavioral study through intelligent image analysis is becoming increasingly vital in an...

A novel scheme for non-invasive drug delivery with a magnetically controlled drug delivering capsule endoscope.

There is a lack of effective means for precise drug delivery of gastrointestinal diseases. Herein we...

Clinical Bedside Benchmarking Test for Measuring the Total Hemoglobin Concentration.

OBJECTIVE: Accurate total hemoglobin concentration (ctHb) measurement is critical for clinical decis...

Thirty-day mortality risk prediction for geriatric patients undergoing non-cardiac surgery in the surgical intensive care unit.

BACKGROUND: The prediction of mortality for elderly patients undergoing non-cardiac surgeries is a v...

Deep learning for Parkinson's disease classification using multimodal and multi-sequences PET/MR images.

BACKGROUND: We aimed to use deep learning (DL) techniques to accurately differentiate Parkinson's di...

Autonomous air combat decision making via graph neural networks and reinforcement learning.

With the rapid advancement of technology, aerial interaction patterns have become increasingly compl...

Multi-Task Collaborative Assisted Training Method for Grouping Fuzzy Categories Classification of Cervical Cancer Cells.

Cervical cancer is a malignant tumor that endangers women's life and health. While deep learning has...

Emerging use of pulmonary artery and cardiac pressure sensing technology in the management of worsening heart failure events.

Unplanned admissions for worsening heart failure (WHF) are the largest resource cost in heart failur...

UAV-based water pollutants detection and classification framework using multi-modal and multi-sensor ensemble learning.

The massive increment in water pollutants due to the release of plastic, industrial, and household w...

Machine-Learning-Powered, Rapid, Accurate, and Multi-Target Mechanical Metamaterials Inverse Design.

Multi-target inverse design, which involves designing multiple targets with different optimization o...

AER U-Net: attention-enhanced multi-scale residual U-Net structure for water body segmentation using Sentinel-2 satellite images.

The automatic segmentation of water bodies from remote-sensing satellite images offers valuable insi...

Effective integration of multi-omics with prior knowledge to identify biomarkers via explainable graph neural networks.

The rapid growth of multi-omics datasets and the wealth of biological knowledge necessitates the dev...

A Multi-Modal Graph Neural Network Framework for Parkinson's Disease Therapeutic Discovery.

Parkinson's disease (PD) is a complex neurodegenerative disorder lacking effective disease-modifying...

Cross language transformation of free text into structured lobectomy surgical records from a multi center study.

In a recent study, the effectiveness of GPT-4 Omni in transforming lobectomy surgical records into s...

Early Detection and Remote Care of Frailty for Older Adults Living in Sparsely Populated Rural Areas in Hokkaido, Japan: A Case Study.

The global increase in the number of older people aged 65 and over is causing concern in healthcare ...

Preparing for Vascular Surgery Board Certification: A Comparative Study Using Large Language Models.

Introduction and aim Large language models (LLMs) are transforming medical education by offering inn...

Generative AI mitigates representation bias and improves model fairness through synthetic health data.

Representation bias in health data can lead to unfair decisions and compromise the generalisability ...

Probability Score for the Diagnosis of Periprosthetic Joint Infection: Development and Validation of a Practical Multi-analyte Machine Learning Model.

Background and objective The diagnosis of periprosthetic joint infection (PJI) relies on established...

MMsurv: a multimodal multi-instance multi-cancer survival prediction model integrating pathological images, clinical information, and sequencing data.

Accurate prediction of patient survival rates in cancer treatment is essential for effective therape...

Association of Deep Learning-based Chest CT-derived Respiratory Parameters with Disease Progression in Amyotrophic Lateral Sclerosis.

Background Forced vital capacity (FVC) is a standard measure of respiratory function in patients wit...

Unravelling tumour spatiotemporal heterogeneity using spatial multimodal data.

Analysing the genome, epigenome, transcriptome, proteome, and metabolome within the spatial context ...

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