Skip to content

Regarding medical datasets #40

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
lixinying0727 opened this issue Apr 12, 2025 · 1 comment
Open

Regarding medical datasets #40

lixinying0727 opened this issue Apr 12, 2025 · 1 comment

Comments

@lixinying0727
Copy link

Hello, I would like to know how AdaCLIP and other baseline models perform zero-shot anomaly detection on medical datasets that lack normal samples. How does it distinguish between normal and abnormal data?I hope to receive the author's response, thank you very much!

@caoyunkang
Copy link
Owner

Currently, these methods can directly perform anomaly detection in arbitrary data, whether from industrial areas or medical fields. It is important to note that the zero-shot performance of these methods is highly dependent on the diversity of the auxiliary annotated datasets and the learning mechanisms employed. Therefore, if similar patterns are included in the training data, we can expect to achieve better performance on the targeted categories.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants