AIMC Topic: Percutaneous Coronary Intervention

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Digital Subtraction Angiography Image Features under the Deep Learning Algorithm in Cardiovascular Interventional Treatment and Nursing for Vascular Restenosis.

Computational and mathematical methods in medicine Jan 17, 2022
The objective of this study was to explore the application value of digital subtraction angiography (DSA) images optimized by deep learning algorithms in vascular restenosis patients undergoing cardiovascular intervention and their nursing efficacy. ...
Computed Tomography Angiography Coronary Stenosis Adult Male Middle Aged Deep Learning Computational Biology C-Reactive Protein Percutaneous Coronary Intervention Coronary Restenosis Artifacts Angiography, Digital Subtraction Humans Algorithms Female Aged
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Machine learning prediction model of acute kidney injury after percutaneous coronary intervention.

Scientific reports Jan 14, 2022
Acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a significant risk of morbidity and mortality. The traditional risk model provided by the National Cardiovascular Data Registry (NCDR) is useful for predictin...
Research Design Acute Kidney Injury Female Aged Aged, 80 and over Humans Machine Learning Forecasting Area Under Curve Registries Percutaneous Coronary Intervention Japan Risk Male Middle Aged Postoperative Complications Logistic Models Models, Statistical
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Automated segmentation of metal stent and bioresorbable vascular scaffold in intravascular optical coherence tomography images using deep learning architectures.

Physics in medicine and biology Dec 31, 2021
Percutaneous coronary intervention (PCI) with stent placement is a treatment effective for coronary artery diseases. Intravascular optical coherence tomography (OCT) with high resolution is used clinically to visualize stent deployment and restenosis...
Humans Deep Learning Treatment Outcome Tomography, Optical Coherence Coronary Angiography Drug-Eluting Stents Percutaneous Coronary Intervention Stents Absorbable Implants Coronary Vessels
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A machine learning model to predict critical care outcomes in patient with chest pain visiting the emergency department.

BMC emergency medicine Oct 7, 2021
BACKGROUND: Currently, the risk stratification of critically ill patient with chest pain is a challenge. We aimed to use machine learning approach to predict the critical care outcomes in patients with chest pain, and simultaneously compare its perfo...
Female Aged Male Middle Aged Case-Control Studies Humans Machine Learning Retrospective Studies Triage Emergency Service, Hospital Percutaneous Coronary Intervention Chest Pain Critical Care Outcomes
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Clinical Feature-Based Machine Learning Model for 1-Year Mortality Risk Prediction of ST-Segment Elevation Myocardial Infarction in Patients with Hyperuricemia: A Retrospective Study.

Computational and mathematical methods in medicine Jul 5, 2021
Accurate risk assessment of high-risk patients is essential in clinical practice. However, there is no practical method to predict or monitor the prognosis of patients with ST-segment elevation myocardial infarction (STEMI) complicated by hyperuricem...
Prognosis Retrospective Studies ST Elevation Myocardial Infarction Female Humans Percutaneous Coronary Intervention Middle Aged Aged Machine Learning Hyperuricemia Male China Algorithms Heart Disease Risk Factors Computational Biology Logistic Models Area Under Curve
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Risk stratification of ST-segment elevation myocardial infarction (STEMI) patients using machine learning based on lipid profiles.

Lipids in health and disease May 6, 2021
BACKGROUND: Numerous studies have revealed the relationship between lipid expression and increased cardiovascular risk in ST-segment elevation myocardial infarction (STEMI) patients. Nevertheless, few investigations have focused on the risk stratific...
Lipoprotein(a) Apolipoprotein A-I Percutaneous Coronary Intervention Cholesterol, LDL Lipid Metabolism Patient Selection Patient Readmission Cholesterol, HDL Triglycerides Kaplan-Meier Estimate Apolipoprotein B-100 Middle Aged Risk Assessment Unsupervised Machine Learning Humans Principal Component Analysis ST Elevation Myocardial Infarction Prognosis Female Aged Male
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Is Deep Learning Coming to Guide Your Coronary Intervention?

JACC. Cardiovascular interventions Apr 14, 2021
Humans Deep Learning Treatment Outcome Coronary Angiography Percutaneous Coronary Intervention
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Machine Learning Identifies Metabolic Signatures that Predict the Risk of Recurrent Angina in Remitted Patients after Percutaneous Coronary Intervention: A Multicenter Prospective Cohort Study.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 8, 2021
Recurrent angina (RA) after percutaneous coronary intervention (PCI) has few known risk factors, hampering the identification of high-risk populations. In this multicenter study, plasma samples are collected from patients with stable angina after PCI...
Humans Percutaneous Coronary Intervention Tandem Mass Spectrometry Angina, Stable Recurrence Male Middle Aged Machine Learning Risk Assessment Chromatography, Liquid Prospective Studies Metabolome Biomarkers Female Risk Factors
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Risk factors associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention: a 10-year follow-up comparing random survival forest and Cox proportional-hazards model.

BMC cardiovascular disorders Jan 18, 2021
BACKGROUND: Due to the limited number of studies with long term follow-up of patients undergoing Percutaneous Coronary Intervention (PCI), we investigated the occurrence of Major Adverse Cardiac and Cerebrovascular Events (MACCE) during 10 years of f...
Time Factors Treatment Outcome Percutaneous Coronary Intervention Coronary Artery Disease Iran Stents Cerebrovascular Disorders Heart Diseases Proportional Hazards Models Risk Factors Aged Male Middle Aged Risk Assessment Machine Learning Decision Support Techniques Retrospective Studies Female Humans
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Artificial neural network-based prediction of prolonged length of stay and need for post-acute care in acute coronary syndrome patients undergoing percutaneous coronary intervention.

European journal of clinical investigation Nov 29, 2020
BACKGROUND: Prolonged length of stay (LOS) and post-acute care after percutaneous coronary intervention (PCI) is common and costly. Risk models for predicting prolonged LOS and post-acute care have limited accuracy. Our goal was to develop and valida...
Hospitals, Rehabilitation ST Elevation Myocardial Infarction Percutaneous Coronary Intervention Patient Discharge Acute Coronary Syndrome Nursing Homes Angina, Unstable Male Humans Transitional Care Middle Aged Neural Networks, Computer Skilled Nursing Facilities Risk Assessment Female Subacute Care Length of Stay Aged Hospices Non-ST Elevated Myocardial Infarction
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