“Artificial intelligence in medical imaging (AIMI) ranking” project is the research initiative supported by Osimis and led by Chief innovation officer Prof. Dr. Sergey Morozov. Dr. Pavel Gelezhe reviews the papers and collects the relevant data.
AIMI-ranking by Osimis aims to create a unified, regularly updated database of AIMI-solutions’ accuracy metrics, as reported in peer-reviewed publications. With this project we provide guidance to clinical users who are comparing and selecting AI-solutions relevant for their clinical practice. Moreover, we hope to motivate AI-vendors to follow the metrics provided by AIMI-ranking and improve the quality of their solutions. The top-tier of AIMI-ranking is provided via Osimis AI-platform.
Best fit of AI-solution for the clinical scenarios is defined by sensitivity > 95% and specificity > 90%. Conditional fit corresponds to AI-solutions with reported sensitivity > 90% and specificity > 80%. Certainly, the real-world performance of certified AI-solutions depends on the pre-test prevalence of a disease, i.e. screening applications require the highest achievable sensitivity. The quality of the publication should also be assessed according to the published methodologies, such as CLAIM.
Read more about the study methodology in our blog.
Version 1.0 published on September 6, 2023 presents data on AI for the interpretation of Mammography, Chest XR, Trauma XR, and Prostate MRI.
Disclaimer: The AIMI-ranking database presents the metrics collected from research papers published in peer-reviewed journals. In case of an author’s discontent with the data presentation please email us.