AIMC Topic: Chest Pain
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Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome.
BMJ health & care informatics
Jun 6, 2025
OBJECTIVES: Most patients presenting with chest pain in the emergency medical services (EMS) setting are suspected of non-ST-elevation acute coronary syndrome (NSTE-ACS). Distinguishing true NSTE-ACS from non-cardiac chest pain based solely on the EC...
Machine learning to risk stratify chest pain patients with non-diagnostic electrocardiogram in an Asian emergency department.
Annals of the Academy of Medicine, Singapore
Apr 22, 2025
INTRODUCTION: Elevated troponin, while essential for diagnosing myocardial infarction, can also be present in non-myocardial infarction conditions. The myocardial-ischaemic-injury-index (MI3) algorithm is a machine learning algorithm that considers a...
AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.
Journal of Korean medical science
Mar 31, 2025
This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively...
Human-centred AI for emergency cardiac care: Evaluating RAPIDx AI with PROLIFERATE_AI.
International journal of medical informatics
Jan 28, 2025
BACKGROUND: Chest pain diagnosis in emergency care is hindered by overlapping cardiac and non-cardiac symptoms, causing diagnostic uncertainty. Artificial Intelligence, such as RAPIDx AI, aims to enhance accuracy through clinical and biochemical data...
Preclinical identification of acute coronary syndrome without high sensitivity troponin assays using machine learning algorithms.
Scientific reports
Apr 29, 2024
Preclinical management of patients with acute chest pain and their identification as candidates for urgent coronary revascularization without the use of high sensitivity troponin essays remains a critical challenge in emergency medicine. We enrolled ...
Deep learning-based diagnosis of aortic dissection using an electrocardiogram: Development, validation, and clinical implications of the AADE score.
Kardiologia polska
Jan 17, 2024
BACKGROUND: Aortic dissection (AD) is frequently associated with abnormalities in electrocardiographic findings. Advancements in medical technology present an opportunity to leverage these observations to improve patient diagnosis and care.
Triaging: Another Vital Application of the Deep Learning Technique on Chest Radiographs at the Emergency Department.
Radiology
Jan 17, 2023
Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.
Radiology
Jan 17, 2023
Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coronary syndrome (ACS), pulmonary embolism (PE), or aortic dissection (AD), often yielding negative resu...
Finding the influential clinical traits that impact on the diagnosis of heart disease using statistical and machine-learning techniques.
Scientific reports
Nov 23, 2022
In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With the correct and quick diagnosis, both mortality and morbidity from cardiac disorders can be dramatically reduced. However, frequent medical check-ups are p...
Initial experience of a deep learning application for the differentiation of Kikuchi-Fujimoto's disease from tuberculous lymphadenitis on neck CECT.
Scientific reports
Aug 19, 2022
Neck contrast-enhanced CT (CECT) is a routine tool used to evaluate patients with cervical lymphadenopathy. This study aimed to evaluate the ability of convolutional neural networks (CNNs) to classify Kikuchi-Fujimoto's disease (KD) and cervical tube...
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