metadata
license: mit
widget:
- src: >-
https://www.verywellhealth.com/thmb/yCmWnfp16fvO0C7qB2jUUcUq8XY=/1500x0/filters:no_upscale():max_bytes(150000):strip_icc()/GettyImages-1451577990-07db16e0a41043bc968d5cbf2dbaec83.jpg
candidate_labels: dark color, light color, irregular shape
example_title: Malignant Melanoma
library_name: open_clip
pipeline_tag: zero-shot-image-classification
Model Card for WhyLesionClip
Table of Contents
Model Details
- Model: WhyLesionClip
- Paper: https://arxiv.org/pdf/2405.14839
- Website: https://yueyang1996.github.io/knobo/
- Repository: https://github.com/YueYANG1996/KnoBo
How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
Uses
Direct Use
[More Information Needed]
Downstream Use
[More Information Needed]
Out-of-Scope Use
[More Information Needed]
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
Training Details
Training Data
[More Information Needed]
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Evaluation
Testing Data
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Citation
BibTeX:
@article{yang2024textbook,
title={A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis},
author={Yue Yang and Mona Gandhi and Yufei Wang and Yifan Wu and Michael S. Yao and Chris Callison-Burch and James C. Gee and Mark Yatskar},
journal={arXiv preprint arXiv:2405.14839},
year={2024}
}