Piotr J. Slomka

Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist

2020 · 210 Zit. · JACC. Cardiovascular imaging

Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines)

2022 · 100 Zit. · Journal of Nuclear Medicine

Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development

2021 · 90 Zit. · Journal of Nuclear Medicine

Artificial intelligence: improving the efficiency of cardiovascular imaging

2020 · 49 Zit. · Expert Review of Medical Devices

Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry

2022 · 39 Zit. · Computers in Biology and Medicine

Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging

2023 · 28 Zit. · JACC. Cardiovascular imaging

Evaluating AI proficiency in nuclear cardiology: Large language models take on the board preparation exam

2024 · 15 Zit. · Journal of Nuclear Cardiology

Evaluating AI Proficiency in Nuclear Cardiology: Large Language Models take on the Board Preparation Exam

2024 · 6 Zit. · medRxiv

Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care

2023 · 3 Zit. · SSRN Electronic Journal

Observational study of sudden cardiac arrest risk (OSCAR): Rationale and design of an electronic health records cohort

2025 · 3 Zit. · IJC Heart & Vasculature

Priming with specific context improves large language model performance on nuclear cardiology board preparation test

2025 · 2 Zit. · Journal of Nuclear Cardiology

AI-based identification of patients who benefit from revascularization: a multicenter study

2025 · 1 Zit. · medRxiv

LONG-TERM PREDICTION OF CARDIAC EVENTS IN ASYMPTOMATIC SUBJECTS BY INTEGRATING NOVEL CIRCULATING AND IMAGING BIOMARKERS USING MACHINE LEARNING

2020 · 0 Zit. · Journal of the American College of Cardiology