AIMC Topic: Acute Coronary Syndrome

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Prediction of disorders with significant coronary lesions using machine learning in patients admitted with chest symptom.

PloS one Oct 10, 2022
BACKGROUND: The early prediction of significant coronary artery lesion, including coronary vasospasm, have yet to be studied. It is essential to discern the disorders with significant coronary lesions (SCDs) requiring coronary angiography from mimick...
Thorax Humans Machine Learning Emergency Service, Hospital Coronary Angiography Acute Coronary Syndrome
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Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients.

PloS one Jan 24, 2022
Acute coronary syndromes (ACS) are a leading cause of deaths worldwide, yet the diagnosis and treatment of this group of diseases represent a significant challenge for clinicians. The epidemiology of ACS is extremely complex and the relationship betw...
Aged Male Middle Aged Risk Assessment Humans Machine Learning Female Acute Coronary Syndrome Patient Admission Models, Cardiovascular Middle East Comorbidity Hospital Mortality Registries Anemia
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Application of Artificial Intelligence in Acute Coronary Syndrome: A Brief Literature Review.

Advances in therapy Sep 15, 2021
Artificial intelligence (AI) is defined as a set of algorithms and intelligence to try to imitate human intelligence. Machine learning is one of them, and deep learning is one of those machine learning techniques. The application of AI in healthcare ...
Machine Learning Algorithms Delivery of Health Care Acute Coronary Syndrome Humans Artificial Intelligence
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Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.

Scientific reports Sep 15, 2021
Our aim was to investigate the usefulness of machine learning approaches on linked administrative health data at the population level in predicting older patients' one-year risk of acute coronary syndrome and death following the use of non-steroidal ...
Risk Factors Male Risk Assessment Comorbidity Humans Machine Learning Prognosis Female Acute Coronary Syndrome Proportional Hazards Models Disease Susceptibility Anti-Inflammatory Agents, Non-Steroidal Area Under Curve ROC Curve Cause of Death Models, Theoretical Disease Management Australia
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A soft voting ensemble classifier for early prediction and diagnosis of occurrences of major adverse cardiovascular events for STEMI and NSTEMI during 2-year follow-up in patients with acute coronary syndrome.

PloS one Jun 11, 2021
OBJECTIVE: Some researchers have studied about early prediction and diagnosis of major adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this paper proposes a soft voting ensemble classifier (SVE) using machine lear...
Area Under Curve ST Elevation Myocardial Infarction Acute Coronary Syndrome Republic of Korea Female Humans Aged Machine Learning Male Middle Aged Algorithms ROC Curve Follow-Up Studies Non-ST Elevated Myocardial Infarction
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In Search of an Optimal Subset of ECG Features to Augment the Diagnosis of Acute Coronary Syndrome at the Emergency Department.

Journal of the American Heart Association Jan 17, 2021
Background Classical ST-T waveform changes on standard 12-lead ECG have limited sensitivity in detecting acute coronary syndrome (ACS) in the emergency department. Numerous novel ECG features have been previously proposed to augment clinicians' decis...
Acute Coronary Syndrome Female Male Middle Aged Decision Support Systems, Clinical Electrocardiography Follow-Up Studies Humans Predictive Value of Tests Machine Learning Emergency Service, Hospital Algorithms Prospective Studies
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Treatment effect prediction with adversarial deep learning using electronic health records.

BMC medical informatics and decision making Dec 14, 2020
BACKGROUND: Treatment effect prediction (TEP) plays an important role in disease management by ensuring that the expected clinical outcomes are obtained after performing specialized and sophisticated treatments on patients given their personalized cl...
Humans Electronic Health Records Acute Coronary Syndrome Deep Learning Logistic Models Heart Failure
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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...
Angina, Unstable Transitional Care Skilled Nursing Facilities Subacute Care Hospices Hospitals, Rehabilitation Percutaneous Coronary Intervention Patient Discharge Aged Acute Coronary Syndrome Male Length of Stay Nursing Homes Humans Middle Aged Non-ST Elevated Myocardial Infarction Neural Networks, Computer Risk Assessment ST Elevation Myocardial Infarction Female
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Calprotectin and Neutrophil Gelatinase-Associated Lipocalin As Biomarkers of Acute Kidney Injury in Acute Coronary Syndrome.

The American journal of the medical sciences Nov 2, 2020
BACKGROUND: Acute kidney injury (AKI) is increasingly being seen in patients with acute coronary syndromes (ACS) and it is associated with higher short-term and long-term morbidity and mortality. Therefore, it is of paramount importance to identify t...
Middle Aged Leukocyte L1 Antigen Complex Cohort Studies Lipocalin-2 Acute Coronary Syndrome Humans Prospective Studies Biomarkers Acute Kidney Injury Female Aged Male
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Machine Learning Improves the Identification of Individuals With Higher Morbidity and Avoidable Health Costs After Acute Coronary Syndromes.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research Oct 12, 2020
OBJECTIVES: Traditional risk scores improved the definition of the initial therapeutic strategy in acute coronary syndrome (ACS), but they were not designed for predicting long-term individual risks and costs. In parallel, attempts to directly predic...
Treatment Outcome Morbidity Acute Coronary Syndrome Health Care Costs Risk Factors Cost Savings Humans Aged Machine Learning Male Female
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