AIMC Topic: Chest Pain

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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...
Humans Machine Learning Retrospective Studies Female Triage Emergency Service, Hospital Percutaneous Coronary Intervention Chest Pain Critical Care Outcomes Aged Male Middle Aged Case-Control Studies
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Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review.

PloS one Aug 24, 2021
BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency department (ED). There are many causes of chest pain, and it is important for the emergency physician to quickly and accurately diagnose life threatening cause...
Diagnosis, Computer-Assisted Predictive Value of Tests Emergency Service, Hospital Myocardial Infarction Chest Pain Humans Machine Learning Risk Factors
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Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study.

The Lancet. Digital health Jul 29, 2021
BACKGROUND: Self-reported symptoms during the COVID-19 pandemic have been used to train artificial intelligence models to identify possible infection foci. To date, these models have only considered the culmination or peak of symptoms, which is not s...
Humans Anosmia Adult Female Dyspnea Artificial Intelligence Adolescent Sensitivity and Specificity SARS-CoV-2 United Kingdom Pandemics Male Mobile Applications Early Diagnosis Aged COVID-19 Middle Aged Models, Biological Epidemiologic Studies Prospective Studies Aged, 80 and over Self Report Young Adult Chest Pain
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Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico.

International journal of environmental research and public health Feb 23, 2021
Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders, and the most deadly: Cardiovascular diseases. Due to the limited space in the emergency department, it is important to identify when thoracic pain is...
Middle Aged Mexico Emergency Service, Hospital Chest Pain Humans Artificial Intelligence Machine Learning Aged
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Deep convolutional neural networks to predict cardiovascular risk from computed tomography.

Nature communications Jan 29, 2021
Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment....
Calcium Chest Pain Heart Disease Risk Factors Coronary Vessels Asymptomatic Diseases Risk Assessment Deep Learning Image Processing, Computer-Assisted Follow-Up Studies Humans Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Male Cardiovascular Diseases Middle Aged
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Extracting Angina Symptoms from Clinical Notes Using Pre-Trained Transformer Architectures.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Anginal symptoms can connote increased cardiac risk and a need for change in cardiovascular management. In this study, a pre-trained transformer architecture was used to automatically detect and characterize anginal symptoms from within the history o...
Electronic Health Records Male Middle Aged Computer Systems Primary Health Care Natural Language Processing Chest Pain Data Collection Documentation Humans Physicians, Primary Care Angina Pectoris
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Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain.

Scandinavian journal of trauma, resuscitation and emergency medicine Sep 11, 2020
BACKGROUND: A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in ...
Mortality Sensitivity and Specificity Male Middle Aged Risk Assessment Models, Statistical Algorithms Taiwan Humans Female Emergency Service, Hospital Artificial Intelligence Aged Myocardial Infarction Young Adult Chest Pain Adult
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SPICED-ACS: Study of the potential impact of a computer-generated ECG diagnostic algorithmic certainty index in STEMI diagnosis: Towards transparent AI.

Journal of electrocardiology Aug 13, 2019
BACKGROUND: Computerised electrocardiogram (ECG) interpretation diagnostic algorithms have been developed to guide clinical decisions like with ST segment elevation myocardial infarction (STEMI) where time in decision making is critical. These comput...
Computers Electrocardiography ST Elevation Myocardial Infarction Chest Pain Humans Artificial Intelligence
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Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients.

PloS one Jan 9, 2019
BACKGROUND: Patient with acute coronary syndrome benefits from early revascularization. However, methods for the selection of patients who require urgent revascularization from a variety of patients visiting the emergency room with chest symptoms is ...
Myocardial Revascularization Decision Making, Computer-Assisted Humans Neural Networks, Computer Emergency Service, Hospital Time Factors Prognosis Patient Selection Sensitivity and Specificity Electrocardiography Chest Pain Diagnosis, Differential Diagnosis, Computer-Assisted Acute Coronary Syndrome Predictive Value of Tests Datasets as Topic
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Diagnosis of Acute Coronary Syndrome with a Support Vector Machine.

Journal of medical systems Jan 27, 2016
Acute coronary syndrome (ACS) is a serious condition arising from an imbalance of supply and demand to meet myocardium's metabolic needs. Patients typically present with retrosternal chest pain radiating to neck and left arm. Electrocardiography (ECG...
Sex Factors Male Electrocardiography Risk Factors Humans Acute Coronary Syndrome Support Vector Machine Middle Aged Aged Neural Networks, Computer Age Factors Troponin I Aged, 80 and over Decision Support Systems, Clinical Female Bayes Theorem Creatine Kinase, MB Form Adult Reproducibility of Results Logistic Models Chest Pain
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