Fátima Rodríguez

Appropriateness of Cardiovascular Disease Prevention Recommendations Obtained From a Popular Online Chat-Based Artificial Intelligence Model

2023 · 469 Zit. · JAMA

Promise and Perils of Big Data and Artificial Intelligence in Clinical Medicine and Biomedical Research

2018 · 35 Zit. · Circulation Research

Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients

2021 · 33 Zit. · Open Heart

Using deep learning-based natural language processing to identify reasons for statin nonuse in patients with atherosclerotic cardiovascular disease

2022 · 24 Zit. · Communications Medicine

Access to digital health technologies: personalized framework and global perspectives

2025 · 15 Zit. · Nature Reviews Cardiology

Artificial intelligence tools in supporting healthcare professionals for tailored patient care

2025 · 14 Zit. · npj Digital Medicine

Natural language processing to identify reasons for sex disparity in statin prescriptions

2023 · 11 Zit. · American Journal of Preventive Cardiology

Testing the Appropriateness of Diabetes Prevention and Care Information Given by the Online Conversational AI ChatGPT

2023 · 5 Zit. · Clinical Diabetes

Understanding Reasons for Oral Anticoagulation Nonprescription in Atrial Fibrillation Using Large Language Models

2025 · 3 Zit. · Journal of the American Heart Association

Leveraging large language models to bridge the digital divide in cardiovascular health research

2025 · 0 Zit. · npj Cardiovascular Health

Abstract 4366575: Performance Benchmarking of Smaller Language Models Against GPT-4 for Predicting Reasons for Oral Anticoagulation Nonprescription in Atrial Fibrillation

2025 · 0 Zit. · Circulation

TOPICS AND SENTIMENTS AROUND STATINS ON REDDIT USING ARTIFICIAL INTELLIGENCE

2023 · 0 Zit. · Journal of the American College of Cardiology

Abstract 15898: Appropriateness of Cardiology Clinic Notes Transcribed by a Popular, Publicly Available Artificial Intelligence Model (GPT-4)

2023 · 0 Zit. · Circulation

Evaluating Large Language Models and Retrieval-Augmented Generation Enhancement for Delivering Guideline-Adherent Nutrition Information for Cardiovascular Disease Prevention: Cross-Sectional Study (Preprint)

2025 · 0 Zit.

Abstract 4361453: Inaccurate information regarding cardiovascular disease prevention enabled by generative artificial intelligence

2025 · 0 Zit. · Circulation