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Heart Arrest

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Smart Cardiac Framework for an Early Detection of Cardiac Arrest Condition and Risk.

Frontiers in public health
Cardiovascular disease (CVD) is considered to be one of the most epidemic diseases in the world today. Predicting CVDs, such as cardiac arrest, is a difficult task in the area of healthcare. The healthcare industry has a vast collection of datasets f...

Development and validation of a deep-learning-based pediatric early warning system: A single-center study.

Biomedical journal
BACKGROUND: Early detection and prompt intervention for clinically deteriorating events are needed to improve clinical outcomes. There have been several attempts at this, including the introduction of rapid response teams (RRTs) with early warning sc...

Accuracy of Machine Learning Models to Predict In-hospital Cardiac Arrest: A Systematic Review.

Clinical nurse specialist CNS
PURPOSE/AIMS: Despite advances in healthcare, the incidence of in-hospital cardiac arrest (IHCA) has continued to rise for the past decade. Identifying those patients at risk has proven challenging. Our objective was to conduct a systematic review of...

Robot-Assisted Totally Endoscopic Mitral Valve Plasty and Coronary Artery Bypass Grafting.

The Annals of thoracic surgery
We experienced 3 cases of port-access robot-assisted totally endoscopic technique for mitral valve repair and concomitant coronary artery bypass. The right internal mammary artery was harvested, mitral valve was fixed, and the right internal mammary ...

Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches large...

Auditory stimulation and deep learning predict awakening from coma after cardiac arrest.

Brain : a journal of neurology
Assessing the integrity of neural functions in coma after cardiac arrest remains an open challenge. Prognostication of coma outcome relies mainly on visual expert scoring of physiological signals, which is prone to subjectivity and leaves a considera...

Development of a high fidelity, multidisciplinary, crisis simulation model for robotic surgical teams.

Journal of robotic surgery
Immediate access to the patient in crisis situations, such as cardiac arrest during robotic surgery, can be challenging. We aimed to present a full immersion simulation module to train robotic surgical teams to manage a crisis scenario, enhance teamw...

Prospective, multicenter validation of the deep learning-based cardiac arrest risk management system for predicting in-hospital cardiac arrest or unplanned intensive care unit transfer in patients admitted to general wards.

Critical care (London, England)
BACKGROUND: Retrospective studies have demonstrated that the deep learning-based cardiac arrest risk management system (DeepCARS™) is superior to the conventional methods in predicting in-hospital cardiac arrest (IHCA). This prospective study aimed t...