Critical Care

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

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Subcategories: Sepsis
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An Enhanced Protocol to Expand Human Exposome and Machine Learning-Based Prediction for Methodology Application.

The human exposome remains limited due to the challenging analytical strategies used to reveal low-l...

Joint Energy-Based Model for Semi-Supervised Respiratory Sound Classification: A Method of Insensitive to Distribution Mismatch.

Semi-supervised learning effectively mitigates the lack of labeled data by introducing extensive unl...

Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm.

The healthcare industry is generating a massive volume of data, promising a potential goldmine of in...

Learning robust medical image segmentation from multi-source annotations.

Collecting annotations from multiple independent sources could mitigate the impact of potential nois...

Explainable AI-driven scalogram analysis and optimized transfer learning for sleep apnea detection with single-lead electrocardiograms.

Sleep apnea, a fatal sleep disorder causing repetitive respiratory cessation, requires immediate int...

Characterizing drivers of change in intraoperative cerebral saturation using supervised machine learning.

Regional cerebral oxygen saturation (rSO) is used to monitor cerebral perfusion with emerging eviden...

Application of artificial intelligence and machine learning in bovine respiratory disease prevention, diagnosis, and classification.

Bovine respiratory disease (BRD) is the leading infectious disease in cattle, resulting in significa...

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

BACKGROUND: Mumps is a viral respiratory disease characterized by facial swelling and transmitted th...

Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019-2023.

OBJECTIVES: To describe the deployment of pediatric Calculated Assessment of Risk and Triage (pCART)...

Class-aware multi-level attention learning for semi-supervised breast cancer diagnosis under imbalanced label distribution.

Breast cancer affects a significant number of patients worldwide, and early diagnosis is critical fo...

A multi-domain feature fusion epilepsy seizure detection method based on spike matching and PLV functional networks.

The identification of spikes, as a typical characteristic wave of epilepsy, is crucial for diagnosin...

Multi-source sparse broad transfer learning for parkinson's disease diagnosis via speech.

Diagnosing Parkinson's disease (PD) via speech is crucial for its non-invasive and convenient data c...

Neural mechanisms, influencing factors and interventions in empathic pain.

Empathic pain, defined as the emotional resonance with the suffering of others, is akin to the obser...

Fast finite-time quantized control of multi-layer networks and its applications in secure communication.

This paper introduces a quantized controller to address the challenge of fast finite-time synchroniz...

Multimodal convolutional neural networks for the prediction of acute kidney injury in the intensive care.

Increased monitoring of health-related data for ICU patients holds great potential for the early pre...

Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.

The revolutionary CRISPR-Cas9 system leverages a programmable guide RNA (gRNA) and Cas9 proteins to ...

Modeling the latent impacts of extreme floods on indoor mold spores in residential buildings: Application of machine learning algorithms.

Floods can severely impact the economy, environment and society. These impacts can be direct and ind...

A Multi-Perspective Self-Supervised Generative Adversarial Network for FS to FFPE Stain Transfer.

In clinical practice, frozen section (FS) images can be utilized to obtain the immediate pathologica...

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