Development of an AI/ML-ready knee ultrasound dataset in a population-based cohort

About this data An ultrasound dataset to use in the discovery of ultrasound features associated with pain and radiographic change in KOA is highly innovative and will be a major step forward for the field. These ultrasound images originate from the diverse and inclusive population-based Johnston County Health Study (JoCoHS). This dataset is designed to adhere to FAIR principles and was funded in part by an Administrative Supplement to Improve the AI/ML-Readiness of NIH-Supported Data (3R01AR077060-03S1).
Working with this dataset WorkingWithTheDataset.ipynb Jupyter notebook If you are familiar with working with Jupyter notebooks, we recommend using the `WorkingWithTheDataset.ipynb` Jupyter notebook to retrieve, validate, and learn more about the dataset. You should downloading the latest `WorkingWithTheDataset.ipynb` file and uploading it to an online Jupyter environment such as https://colab.research.google.com or use the notebook in your Jupyter environment of choice. You will also need to download the `CONFIGURATION_SETTINGS.template.md` file from this dataset since the contents are used to configure the Jupyter notebook. Note: at the time of this writing, we do not recommend using Binder (mybinder.org) if you are interested in only reviewing the WorkingWithTheDataset.ipynb notebook. When Binder loads the dataset, it will download all files from this dataset, resulting in a long build time. However, if you plan to work with all files in the dataset then Binder might work for you. We do not offer support for this service or other Jupyter Lab environments.
Metadata The `DatasetMetadata.json` file contains general information about the files and variables within this dataset. We use it as our validation metadata to verify the data we are importing into this Dataverse dataset. This file is also the most comprehensive with regards to the dataset metadata.
Data collection in progress This dataset is not complete and will be updated regularly as additional data is collected.

### 数据集概况
本数据集为超声数据集，旨在探索与膝骨关节炎（Knee Osteoarthritis, KOA）患者疼痛及影像学改变相关的超声特征，具有极高的创新性，将为本领域带来重要突破。本数据集的超声影像来源于覆盖多元包容人群的约翰斯顿县健康研究（Johnston County Health Study, JoCoHS）。本数据集严格遵循FAIR原则构建，且获得了用于提升美国国立卫生研究院（National Institutes of Health, NIH）支持数据的AI/机器学习适配性的行政补充资助（项目编号：3R01AR077060-03S1）。

### 数据集使用方法
本项目附带`WorkingWithTheDataset.ipynb` Jupyter Notebook脚本。若您熟悉Jupyter Notebook的使用，我们推荐通过该脚本获取、验证数据集并深入了解数据集详情。您需下载最新版的`WorkingWithTheDataset.ipynb`文件，并将其上传至在线Jupyter环境（如https://colab.research.google.com），或在您自选的本地Jupyter环境中运行该脚本。此外，您还需从本数据集中下载`CONFIGURATION_SETTINGS.template.md`文件，该文件的配置内容将用于设置Jupyter Notebook脚本。
注意：在本文撰写之时，若您仅需查看`WorkingWithTheDataset.ipynb`脚本，我们不推荐使用Binder（mybinder.org）。因为Binder加载数据集时会下载本数据集的全部文件，导致构建耗时过长。但若您计划使用本数据集的全部文件，则Binder可满足需求。本团队不针对该服务或其他Jupyter Lab环境提供技术支持。

### 元数据
`DatasetMetadata.json`文件包含本数据集内所有文件与变量的通用信息。我们将其作为验证元数据，用于核查导入至本Dataverse数据集的各项数据。该文件也是本数据集元数据最为全面的载体。

### 数据采集进度说明
本数据集尚未完成，后续将随着新增数据的采集定期更新。