Pitfalls and Best Practices in Evaluation of AI Algorithmic Biases in Radiology
Paul H. Yi, Preetham Bachina, Beepul Bharti, Sean P. Garin, Adway Kanhere, Pranav Kulkarni, David Li, Vishwa S. Parekh, Samantha M. Santomartino, Linda Moy, Jeremias Sulam
Abstract
statistical evaluations of bias. Although AI bias in radiology has been broadly reviewed in the recent literature, this article focuses specifically on underrecognized potential pitfalls related to the three key areas. By providing awareness of these pitfalls along with actionable practices to avoid them, exciting AI technologies can be used in radiology for the good of all people.
Topics & Concepts
MedicineMEDLINEMedical physicsData scienceArtificial intelligenceRadiologyMachine learningComputer scienceLawPolitical scienceArtificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical ImagingRadiology practices and education