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News Daily News

Plaque Type Equally Predictive of MI in Women and Men: SCOT-HEART

Yael L. Maxwell

April 16, 2021

News Features

AI in Cardiology: Where We Are Now and Where to Go Next

Yael L. Maxwell

March 30, 2021

News Daily News

Meta-analysis Supports Genotype-Guided P2Y12 Prescription for ACS

Yael L. Maxwell

March 25, 2021

News Daily News

To Predict Mortality After MI, Machine Learning Needs Better Intel

Yael L. Maxwell

March 12, 2021

News Daily News

Large US Study Links Air Pollution to Heart, Lung Diseases

Shelley Wood

February 26, 2021

News Daily News

AI Shows Potential for Predicting New-Onset AF from ECGs

Yael L. Maxwell

February 18, 2021

News Daily News

Machine Learning ‘Sniffs’ Out Long QT Otherwise Unseen on ECG

Yael L. Maxwell

February 11, 2021

News Daily News

Based on Machine Learning, PRAISE Score Balances Risks in Post-ACS Care

Yael L. Maxwell

January 26, 2021

News Daily News

Machine Learning Based on ECG, Clinical Data Predicts Coronary Calcium

Todd Neale

December 04, 2020

News Conference News AHA 2020

SCAPIS: CTA Finds Silent CAD in 42% of Middle-aged Adults

Shelley Wood

November 13, 2020

Presentation TCT 2020

TCT 413: Evaluation of the DeepIVUS machine learning platform for automatic detection of stent underexpansion

Presenter: David Molony

October 14, 2020

News Conference News SCCT 2020

Biggest Barriers to Cardiac CT? Old Myths, Fair Payment, and De-adoption

Yael L. Maxwell

July 22, 2020

News Conference News SCCT 2020

ISCHEMIA, Patient Age in PROMISE Among Top CT Papers of the Year at SCCT

Yael L. Maxwell

July 20, 2020

News Features

COVID-19’s Enduring Impact on the Heart? Some Clues and Predictions

Shelley Wood

July 20, 2020

News Daily News

Various Arrythmia Risk-Assessment Tools Streamlined in Multisociety Consensus

Todd Neale

June 22, 2020

News Conference News ACC 2020

Low-Attenuation Plaque Volume Predicts MI in SCOT-HEART Analysis

Shelley Wood

March 23, 2020

News Daily News

Stick-on Sensor Predicts Heart-Failure Hospitalizations: Pilot Study

Shelley Wood

February 26, 2020

News Industry News

FIND FH® Makes Identifying and Diagnosing Individuals at Genetic Risk for Early Heart Attacks and Stroke Possible

October 21, 2019

Presentation TCT 2019

Machine Learning Modelling vs. STS/ACC-TVT Score to Predict Mortality After Transcatheter Aortic Valve Replacement

Presenter: Pavel Overtchouk

September 26, 2019

Presentation TCT 2019

Machine Learning for Risk Prediction of Future Clinical Events in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Presenter: Jin Sup

September 26, 2019

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Plaque Type Equally Predictive of MI in Women and Men: SCOT-HEART

AI in Cardiology: Where We Are Now and Where to Go Next

Meta-analysis Supports Genotype-Guided P2Y12 Prescription for ACS

To Predict Mortality After MI, Machine Learning Needs Better Intel

Large US Study Links Air Pollution to Heart, Lung Diseases

AI Shows Potential for Predicting New-Onset AF from ECGs

Machine Learning ‘Sniffs’ Out Long QT Otherwise Unseen on ECG

Based on Machine Learning, PRAISE Score Balances Risks in Post-ACS Care

Machine Learning Based on ECG, Clinical Data Predicts Coronary Calcium

SCAPIS: CTA Finds Silent CAD in 42% of Middle-aged Adults

TCT 413: Evaluation of the DeepIVUS machine learning platform for automatic detection of stent underexpansion

Biggest Barriers to Cardiac CT? Old Myths, Fair Payment, and De-adoption

ISCHEMIA, Patient Age in PROMISE Among Top CT Papers of the Year at SCCT

COVID-19’s Enduring Impact on the Heart? Some Clues and Predictions

Various Arrythmia Risk-Assessment Tools Streamlined in Multisociety Consensus

Low-Attenuation Plaque Volume Predicts MI in SCOT-HEART Analysis

Stick-on Sensor Predicts Heart-Failure Hospitalizations: Pilot Study

FIND FH® Makes Identifying and Diagnosing Individuals at Genetic Risk for Early Heart Attacks and Stroke Possible

Machine Learning Modelling vs. STS/ACC-TVT Score to Predict Mortality After Transcatheter Aortic Valve Replacement

Machine Learning for Risk Prediction of Future Clinical Events in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

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