This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Chen Yan and researcher Sun Qibin from the University of Science and Technology of China (USTC) achieved contactless electrocardiogram (ECG) monitoring through a millimeter-wave radar system. Recently, a team led by Prof. Their work was published in IEEE Transactions on Mobile Computing and reported by IEEE Spectrum.
VTT Technical Research Centre of Finland has developed a new sustainable electrocardiogram (ECG, also known as EKG) patch that is fully recyclable and made of biomaterials. The device is modular, so electronic components can be easily removed from the disposable patch and used again.
Researchers used an AI-enabled digital stethoscope that captures electrocardiogram ( ECG ) data and heart sounds to identify twice as many cases of peripartum cardiomyopathy as compared to regular care, according to a news release from the American Heart Association.
Electrocardiogram tests may someday be used with an artificial intelligence (AI) model to detect premature aging and cognitive decline, according to a preliminary study presented at the American Stroke Association's International Stroke Conference 2025, held in Los Angeles, Feb. 57, 2025.
Background Researchers have developed machine learning-based ECG diagnostic algorithms that match or even surpass cardiologist level of performance. However, most of them cannot be used in real-world, as older generation ECG machines do not permit installation of new algorithms.
Mount Sinai researchers have developed an innovative artificial intelligence (AI) model for electrocardiogram (ECG) analysis that allows for the interpretation of ECGs as language.
An electrocardiogram demonstrated sinus rhythm with T-wave alterations and a V2R/S ratio greater than 1. This case underscores the significance of considering Kounis syndrome in patients with a history of infection or allergies who present with chest pain, emphasizing the necessity for thorough clinical evaluation and continued research.
Now, researchers and clinicians at Mayo Clinic are using artificial intelligence (AI) technology to flag heart problems earlier, boosting the abilities of a diagnostic test that has been around for over a century—the electrocardiogram (ECG).
ObjectiveTo compare the image quality, radiation dose, and examination time between non-electrocardiogram (ECG)-gated coronary CT angiography (ECG-less CCTA) and conventional ECG-gated CCTA using wide-detector CT, and validate its clinical applicability.MethodsIn this prospective study, 109 patients with suspected coronary artery disease were divided (..)
Further research is imperative to further explore the management and prognosis of TTS following TEER. Subsequent assessment revealed TTS. After receiving the optimal medical therapy, the patient was discharged after 10days without experiencing acute chest pain or shortness of breath.
If zero-shot VQA can be applied to a 12-lead electrocardiogram (ECG), a prevalent diagnostic tool in the medical field, the potential benefits to the field would be substantial. Large Language Models (LLM) are increasingly multimodal, and Zero-Shot Visual Question Answering (VQA) shows promise for image interpretation.
Patients had routine 12-lead electrocardiograms (ECGs) regardless of presenting complaints. Data regarding AF screening in conflict countries emergency departments (ED) is lacking.MethodsWe included consecutive patients >40 years old who reported to the ED of a Syrian tertiary centre between July 2024 and September 2024.
The electrocardiogram (ECG) and electrogram (EGM) parameters were evaluated and other electrophysiological characteristics were analyzed using a three-electrode configuration test.ResultsSeven capture modes [right ventricular septal (RVS)+left ventricular septal (LVS)+LBB, RVS+LBB, LVS+LBB, RVS+LVS, RVS, LVS, and LBB] were utilized in the study.
Thirty day electrocardiogram (ECG) monitoring in patients with hypertrophic cardiomyopathy (HCM) detects more arrhythmias than the standard 24 to 48 hours, according to late breaking science presented at EHRA 2023, a scientific congress of the European Society of Cardiology (ESC).
A new AI model can flag female patients who are at higher risk of heart disease based on an electrocardiogram (ECG). The researchers say the algorithm, designed specifically for female patients, could enable doctors to identify high-risk women earlier, enabling better treatment and care.
That added value should come in handy for Edgewise, which is still planning a lot more research on EDG-7500’s safety, efficacy, and treatment dosages for both oHCM and nHCM. The EDG-7500 groups also had no meaningful changes in LVEF, and none of the subjects experienced a decrease in LVEF <50%.
Research Highlights: In a study of patients in a hospital in Taiwan, artificial intelligence technology paired with electrocardiogram testing reduced the time to diagnose and transfer people with heart attacks to the cardiac catheterization laboratory.
By detecting cardiovascular ailments and helping assess overall cardiac health, wearable electrocardiograms save lives, not to mention exorbitant hospital care costs. Researchers now present a novel wearable electrocardiogram patch for enhanced point-of-care diagnostics.
A new machine learning model uses electrocardiogram (ECG) readings to diagnose and classify heart attacks faster and more accurately than current approaches, according to a study led by University of Pittsburgh researchers that is published in Nature Medicine.
Researchers at the Yale Cardiovascular Data Science (CarDS) Lab have developed an artificial intelligence (AI)-based model for clinical diagnosis that can use electrocardiogram (ECG) images, regardless of format or layout, to diagnose multiple heart rhythm and conduction disorders.
Recent guidelines propose N-terminal pro-B-type natriuretic peptide (NT-proBNP) for recognition of asymptomatic left ventricular (LV) dysfunction (Stage B Heart Failure, SBHF) in type 2 diabetes mellitus (T2DM.
Recent research has identified cases of sustained FAT originating from the interatrial septum (IAS); a subset of cases presents a unique challenge, with foci originating from the peri-patent foramen ovale (peri-PFO), requiring specialized management during catheter ablation.
Electrocardiogram (ECG) signals were continuously recorded throughout the procedure. Further research could enhance these techniques' applicability in clinical settings. Post-surgery, cerebral infarction was confirmed via the triphenyl tetrazolium chloride (TTC) staining technique.
While model evidence-based guidelines (EBG) exist, there is limited research on national adoption. Background:Emergency medical service (EMS) clinicians provide time-sensitive care for patients with suspected stroke. Included are advanced life support agencies with >6 annual strokes.
Introduction:The term headpulse refers to imperceptible head movements associated with each cardiac contraction, as measured by a cranial accelerometry device with electrocardiogram leads.
The last section is a detailed discussion of the research on aVR in both STEMI and NonSTEMI. Updates on the Electrocardiogram in Acute Coronary Syndromes. Electrocardiogram patterns in acute left main coronary artery occlusion. I repeat that ST elevation in aVR is not diagnostic of left main occlusion. References : 1.
Apple has made available in Australia its electrocardiogram app for Series 4, 5 and 6 of its Apple Watch. Data collected by Apple Watch could be used to help diagnose atrial fibrillation early,” said Bill Stavreski, general manager for Heart Health and Research at the Australian Heart Foundation.
This is radically simplifying the patient pathway for Electrocardiogram (ECG) tests. Marco Mazzanti , Scientific Director of International Research Frameworks on Artificial Intelligence in Cardiology, notes, “Pharmacies often serve as accessible points of care for many patients.
can cause ST-segment elevation (STE) on electrocardiogram (ECG), the distinction between them may be hard and complicated. Many researchers, including the editors of this blog, tried to develop such tools in the recent past and we have recommended their use in certain clinical scenarios in many posts on this blog.
In a study published in Communications Medicine , David Ouyang, MD, assistant professor of Cardiology and Medicine at Cedars-Sinai, along with Chugh and fellow investigators trained a deep learning algorithm to study patterns in electrocardiograms, also known as ECGs, which are recordings of the heart’s electrical activity.
I do research on Cardiologs' algorithm: Smith SW et al. A Deep Neural Network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation. Cardiologs founder, Yann Flereau, was named by MIT as the European Innovator of the Year.
This results in severe chest pain or discomfort, with the subsequent release of cardiac biomarkers, and alterations in the electrocardiogram. It can cause diminished heart function and mortality if not treated properly with suitable measures.
milla1cf Wed, 12/13/2023 - 10:24 December 13, 2023 — A new artificial intelligence (AI) model designed by Scripps Research scientists could help clinicians better screen patients for atrial fibrillation (or AFib)—an irregular, fast heartbeat that is associated with stroke and heart failure.
Signify Research has just released a deep-dive qualitative analysis of developments around the use of AI to analyze and interpret electrocardiograms (ECGs), one of the world’s most ubiquitous diagnostic tests for cardiac disease. Prior to Signify Research, Jones gained 13 years of research experience in South Africa.
In this setting, family history of arrhythmia and being carrier of a pathogenic/likely pathogenic variant are the main risk factors for LV systolic dysfunction, while LV global longitudinal strain (LV-GLS) and Holter electrocardiogram (ECG) showed a relevant role in terms of prediction of LV systolic dysfunction and outcomes.
Getty Images milla1cf Mon, 04/01/2024 - 08:21 April 1, 2024 — Roughly 25,000 Americans die each year from valvular heart disease, but researchers from Rutgers Health and other institutions conclude that new technology could soon help doctors slash that number. “We
Workup including routine laboratory results, 12-lead electrocardiogram (ECG), echocardiogram, and coronary angiogram was non-specific. Further research is warranted to investigate the interactions between lacosamide and SCN5A variants. Of note, the patient had a family history of sudden cardiac death.
A simple electrocardiogram (ECG) can pinpoint hospitalized COVID-19 patients at high risk of death who might need intensive management. Specifically, the research showed that a prolonged QT interval on the ECG was an independent risk factor for both myocardial injury and one-year mortality.
Image courtesy of UCL Institute of Cardiovascular Science / James Tye milla1cf Tue, 12/19/2023 - 18:19 December 19, 2023 — A vest that can map the electrical activity of the heart in fine detail could potentially be used to better identify people at high risk of sudden cardiac death , suggests a new study led by UCL researchers.
On September 21, 2024, during the 79th Brazilian Congress of Cardiology in Brasília, we celebrated excellence in research and publication with the SBC Scientific Publication Award for the Family ABC journals!
Laboratory tests showed markedly elevated troponin I levels (>50 ng/ml) and atrial fibrillation, along with inferior wall ST elevation on the electrocardiogram. The medical conundrum of deciding which condition to treat first underscores the need for further research. ml subcutaneously once daily.
Players previously received an electrocardiogram (ECG) performed an average of 239 days before infection. 12-Lead ECG statistics of Athletes In 17 (3%) of the athletes, the researchers discovered de-novo ECG alterations. The population consisted of 88% male players with a mean age of 21 (x̄).
We organize all of the trending information in your field so you don't have to. Join thousands of users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content