Datasets
Standard Dataset
Osteoarthritis Prediction
- Citation Author(s):
- Submitted by:
- Mengjun Tao
- Last updated:
- Tue, 12/26/2023 - 15:05
- DOI:
- 10.21227/ewx7-b315
- License:
128 Views- Categories:
- Keywords:
Abstract
This is an open source data set from Kaggle. The original link is
<a href="https://www.kaggle.com/datasets/farjanakabirsamanta/osteoarthritis-prediction?resource=download">IEEE DataPort</a>
The dataset, provided by the University of Florida and the OAI organisation in September 2018, is 428MB in size and contains 5778 training samples, 1656 test samples and 826 validation samples.
The dataset contains medical images of knees from various patients, including anteroposterior, lateral, and oblique X-ray images as well as magnetic resonance imaging (MRI) scans. Additionally, the dataset provides clinical features associated with each image, such as patient age, gender, pain level, inflammation indicators, etc.
You have to create a deep learning model that can detect if osteoarthritis is present or not in a given knee X-ray image.
The Dataset contains three folders：Test, Train, Valid.
