British Heart Foundation

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods

Karel G.M. Moons, Johanna AAG Damen, T. K. Kaul et al.

2025 · 296 Zit.

Healthcare Big Data in Hong Kong: Development and Implementation of Artificial Intelligence-Enhanced Predictive Models for Risk Stratification

Gary Tse, Quinncy Lee, Oscar Hou In Chou et al.

2023 · 48 Zit.

Artificial intelligence in cardiovascular imaging—principles, expectations, and limitations

Charalambos Antoniades, Evangelos K. Oikonomou

2021 · 36 Zit.

Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging

Damini Dey, Rima Arnaout, Sameer Antani et al.

2023 · 28 Zit.

Towards nationally curated data archives for clinical radiology image analysis at scale: Learnings from national data collection in response to a pandemic

Dominic Cushnan, Rosalind Berka, Ottavia Bertolli et al.

2021 · 14 Zit.

Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-based Segmentation

Esther Puyol‐Antón, Bram Ruijsink, Jorge Mariscal Harana et al.

2021 · 13 Zit.

How will artificial intelligence transform cardiovascular computed tomography? A conversation with an AI model

Michelle C. Williams, James Shambrook

2023 · 12 Zit.

Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management

Antonis A. Armoundas, Faraz S. Ahmad, Zachi I. Attia et al.

2025 · 11 Zit.

Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials

Pablo-Miki Martí Castellote, Christopher Reeder, Brian Claggett et al.

2024 · 8 Zit.

Artificial Intelligence Needs Clinical Intelligence to Succeed

John G.F. Cleland, Charles Li, Yola Jones

2020 · 7 Zit.

AI medical device post-market surveillance regulations: consensus recommendations by the European Society of Radiology

Renato Cuocolo, Diana Bernardini, Daniel Pinto dos Santos et al.

2025 · 6 Zit.

New ways to use imaging data in cardiovascular research: survey of opinions on federated learning and synthetic data

Michelle C. Williams, Jacqueline A. L. MacArthur, Ross Forsyth et al.

2025 · 4 Zit.

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation

Gary S. Collins, Karel G.M. Moons, Paula Dhiman et al.

2025 · 4 Zit.

Big data research is everyone's research—Making epilepsy data science accessible to the global community: Report of the <scp>ILAE</scp> big data commission

Colin B. Josephson, Eleonora Aronica, Sándor Beniczky et al.

2024 · 4 Zit.

Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network

Rupa Makadia, Azza Shoaibi, Gowtham Rao et al.

2023 · 3 Zit.