This paper is in the following e-collection/theme issue:

AI in Older Adult Care (39) Clinical Informatics (1288) Machine Learning (2027) Cardiology (217) Heart Valve Disease Research (6) Natural Language Processing (892) Artificial Intelligence (2052) Frailty Detection, Assessment and Prediction (58)

Published on in Vol 7 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58980, first published .
Enhancing Frailty Assessments for Transcatheter Aortic Valve Replacement Patients Using Structured and Unstructured Data: Real-World Evidence Study

Enhancing Frailty Assessments for Transcatheter Aortic Valve Replacement Patients Using Structured and Unstructured Data: Real-World Evidence Study

Enhancing Frailty Assessments for Transcatheter Aortic Valve Replacement Patients Using Structured and Unstructured Data: Real-World Evidence Study

Authors of this article:

Mamoun T Mardini1 Author Orcid Image ;   Chen Bai1 Author Orcid Image ;   Anthony A Bavry2 Author Orcid Image ;   Ahmed Zaghloul2 Author Orcid Image ;   R David Anderson3 Author Orcid Image ;   Catherine E Crenshaw Price4, 5 Author Orcid Image ;   Mohammad A Z Al-Ani3 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Bai C, Xiao F, Al-Ani M, Price C, Manini T, Mardini M. External validation of an AI-based preoperative frailty index using real-world data. The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences 2025;80(11) View