Timezone: »
Estimating test performance of software AI-based medical devices under distribution shifts is crucial for evaluating safety, efficiency, and usability prior to clinical deployment~\cite{fda}.Due to the nature of regulated medical device software and the difficulty in acquiring large amounts of labeled medical datasets, we consider the task of predicting test accuracy of an arbitrary black-box model on an unlabeled target domain \textit{without} modification to the original training process or any distributional assumptions of the original source data (i.e. we treat the model as a black-box'' and only use the predicted output responses).We propose a
black-box'' test estimation technique based on conformal prediction and evaluate against other methods on three medical imaging datasets (mammography, dermatology, and histopathology) under several clinically relevant types of distribution shift (institution, hardware scanner, atlas, hospital).We hope that by promoting practical and effective estimation techniques for black-box models, manufacturers of medical devices will develop more standardized and realistic evaluation procedures to improve robustness and trustworthiness of clinical AI tools.
Author Information
charlie lu (Martinos center for biomedical imaging)
Syed Rakin Ahmed (Harvard University)
Praveer Singh (MGH / Harvard Medical School)
Jayashree Kalpathy-Cramer (University of Colorado Anchutz Campus)
More from the Same Authors
-
2021 : Evaluating subgroup disparity using epistemic for breast density assessment in mammography »
charlie lu · Andreanne Lemay · Katharina Hoebel · Jayashree Kalpathy-Cramer -
2023 : Conditional Diffusion Replay for Continual Learning in Medical Settings »
Yewon Byun · Saurabh Garg · Sanket Vaibhav Mehta · Praveer Singh · Jayashree Kalpathy-cramer · Bryan Wilder · Zachary Lipton -
2023 : Prompt-based Generative Replay: A Text-to-Image Approach for Continual Learning in Medical Settings »
Yewon Byun · Saurabh Garg · Sanket Vaibhav Mehta · Jayashree Kalpathy-Cramer · Praveer Singh · Bryan Wilder · Zachary Lipton -
2022 : Discussion Panel »
Percy Liang · Léon Bottou · Jayashree Kalpathy-Cramer · Alex Smola -
2022 : Distribution Shifts in Healthcare—A Key Barrier to Safe Deployment of Machine Learning Algorithms in the Clinic »
Jayashree Kalpathy-Cramer