Assessing Radiology Research on Artificial Intelligence: A Brief Guide for Authors, Reviewers, and Readers—From the Radiology Editorial Board

2019/12/31 by David A. Bluemke, Linda Moy, Miriam A. Bredella +8 · 6 citations
Medicine · #Radiomics and Machine Learning in Medical Imaging #Radiology practices and education #Artificial Intelligence in Healthcare and Education

paper · doi:10.1148/radiol.2019192515

Citations

• Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration
• Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

Cited by

• Evaluation of AI Ethics Tools in Language Models: A Developers' Perspective Case Stud
• An Explainable Deep Learning Model for Focal Liver Lesion Diagnosis Using Multiparametric MRI
• Development and Validation of a Sham-AI Model for Intracranial Aneurysm Detection at CT Angiography
• Editorial for “A Multiparametric MRI‐based Radiomics Nomogram for Predicting Lymphovascular Space Invasion in Endometrial Carcinoma”
• Transparency of medical artificial intelligence systems
• Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning
• RTEX: A novel methodology for Ranking, Tagging, and Explanatory diagnostic captioning of radiography exams