AIMC Topic: Acute Coronary Syndrome

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Implementation of a machine learning model in acute coronary syndrome and stroke risk assessment for patients with lower urinary tract symptoms.

Taiwanese journal of obstetrics & gynecology Jul 1, 2024
OBJECTIVE: The global population is aging and the burden of lower urinary tract symptoms (LUTS) is expected to increase. According to the National Health Insurance Research Database, our previous studies have showed LUTS may predispose patients to ca...
Machine Learning Retrospective Studies Female Risk Factors Humans ROC Curve Stroke Acute Coronary Syndrome Lower Urinary Tract Symptoms Aged Male Middle Aged Risk Assessment
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Enhanced Diagnosis of Plaque Erosion by Deep Learning in Patients With Acute Coronary Syndromes.

JACC. Cardiovascular interventions Oct 24, 2022
BACKGROUND: Acute coronary syndromes caused by plaque erosion might be potentially managed conservatively without stenting. Currently, the diagnosis of plaque erosion requires expertise in optical coherence tomographic (OCT) image interpretation. In ...
Tomography, Optical Coherence Humans Acute Coronary Syndrome Cross-Sectional Studies Plaque, Atherosclerotic Deep Learning Treatment Outcome
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Machine learning predicts risk in ACS.

Nature reviews. Cardiology Apr 1, 2021
Humans Machine Learning Acute Coronary Syndrome
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Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets.

Lancet (London, England) Jan 16, 2021
BACKGROUND: The accuracy of current prediction tools for ischaemic and bleeding events after an acute coronary syndrome (ACS) remains insufficient for individualised patient management strategies. We developed a machine learning-based risk stratifica...
Humans Machine Learning Clinical Decision-Making Mortality Postoperative Complications Hemorrhage Acute Coronary Syndrome Datasets as Topic Female Adult Male
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Treatment of individual predictors with neural network algorithms improves Global Registry of Acute Coronary Events score discrimination.

Archivos de cardiologia de Mexico Jan 1, 2021
OBJECTIVE: The aim of this study was to develop, train, and test different neural network (NN) algorithm-based models to improve the Global Registry of Acute Coronary Events (GRACE) score performance to predict in-hospital mortality after an acute co...
Databases, Factual Prognosis Female Aged Humans Neural Networks, Computer Algorithms Acute Coronary Syndrome Male Middle Aged Hospital Mortality Registries
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Concerns for management of STEMI patients in the COVID-19 era: a paradox phenomenon.

Journal of thrombosis and thrombolysis Nov 1, 2020
The pandemic of coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. During this time, the management of people with acute coronary syndromes (ACS) and COVID-19 has become a global issue, especially since...
ST Elevation Myocardial Infarction Percutaneous Coronary Intervention Coronavirus Infections Acute Coronary Syndrome Motor Activity Pneumonia, Viral Infectious Disease Transmission, Patient-to-Professional Personal Protective Equipment Occupational Exposure Treatment Outcome Robotics Thrombolytic Therapy COVID-19 Risk Factors Infection Control Humans Pandemics
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Machine learning versus traditional risk stratification methods in acute coronary syndrome: a pooled randomized clinical trial analysis.

Journal of thrombosis and thrombolysis Jan 1, 2020
Traditional statistical models allow population based inferences and comparisons. Machine learning (ML) explores datasets to develop algorithms that do not assume linear relationships between variables and outcomes and that may account for higher ord...
Risk Assessment Randomized Controlled Trials as Topic Fibrinolytic Agents Hemorrhage Acute Coronary Syndrome Female Models, Cardiovascular Aged Male Humans Middle Aged Machine Learning
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Proton pump inhibitors receiving and prognosis of patients after scheduled percutaneous coronary interventions.

Terapevticheskii arkhiv Sep 20, 2018
AIM: The urgency of the study is determined by the lack of data necessary in order to assess the safety of prolonged use of proton pump inhibitors (PPI) in patients with IHD combined with anti-aggregant therapy. The aim of the study was to study the ...
Risk Adjustment Myocardial Ischemia Platelet Aggregation Inhibitors Proton Pump Inhibitors Registries Female Drug Therapy, Combination Humans Percutaneous Coronary Intervention Aged Prospective Studies Coronary Restenosis Gastrointestinal Hemorrhage Male Acute Coronary Syndrome Russia Prognosis Middle Aged Long Term Adverse Effects
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Machine learning for prediction of 30-day mortality after ST elevation myocardial infraction: An Acute Coronary Syndrome Israeli Survey data mining study.

International journal of cardiology Nov 1, 2017
BACKGROUND: Risk scores for prediction of mortality 30-days following a ST-segment elevation myocardial infarction (STEMI) have been developed using a conventional statistical approach.
Risk Assessment Surveys and Questionnaires Hospital Mortality ROC Curve ST Elevation Myocardial Infarction Registries Data Mining Israel Aged Survival Rate Male Middle Aged Retrospective Studies Female Risk Factors Humans Machine Learning Algorithms Acute Coronary Syndrome Prognosis
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Acute Coronary Syndrome Risk Prediction Based on GRACE Risk Score.

Studies in health technology and informatics Jan 1, 2017
Clinical risk prediction of acute coronary syndrome (ACS) plays a critical role for clinical decision support, treatment management and quality of care assessment in ACS patients. Admission records contain a wealth of patient information in the early...
Humans Algorithms Prognosis Risk Factors Hospitalization Risk Assessment Acute Coronary Syndrome
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