PCOSGen-test dataset

The aim of the Auto-PCOS classification challenge is to provide an opportunity for the development, testing and evaluation of Artificial Intelligence (AI) models for automatic PCOS classification of healthy and un-healthy frames extracted from ultrasound videos. This challenge encompasses diverse training and test datasets, fostering the creation of vendor-agnostic, interpretable, and broadly applicable AI models. The PCOSGen dataset is first of its kind, consists of different training and test datasets which have been collected from multiple internet resources like YouTube, ultrasoundcases.info, and Kaggle. PCOSGen-test consists of 1468 healthy and un-healthy instances. The class labels for the testing dataset are not mentioned. Participants must follow the guidelines mentioned on the website. The Auto-PCOS Classification Challenge is over! Results announced! UPDATE: The test labels have been released! 1 represents healthy. 0 represents un-healthy. For more details: Check 68d601deaac6055bc25b2816fb0b2d39.pdf (d197for5662m48.cloudfront.net) @article{hubauto, title={Auto-PCOS Classification Challenge}, author={Hub, Misa and Handa, Palak and Saini, Anushka and Dutta, Siddhant and Pathak, Harsh and Choudhary, Nishi and Goel, Nidhi and Dhanao, Jasdeep Kaur} }