囊性纤维化相关糖尿病的遗传修饰因子

数据集获取

源站：https://clinicaltrials.gov/study/NCT01113216

标准获取流程：

1. 访问源站链接，注册/登录账号；
2. 进入数据集详情页，按页面指引申请权限或直接下载；
3. 部分平台提供 SDK，例如：
   • OpenDataLab: pip install openxlab 后 openxlab.dataset.get(...)
   • ModelScope: pip install modelscope 后 modelscope download
   • 天池: 登录后页面提供直链下载
     以源站「数据下载/使用文档」页面为准。

数据说明

Conditions: Cystic Fibrosis Related Diabetes. The study is recruiting people with cystic fibrosis (CF). The medical record is being extracted, and a blood sample is taken for DNA. The DNA samples are tested for variation both at the cystic fibrosis transmembrane conductance regulator (CFTR) gene (the CF gene) and over the entire rest of the genome. Using large numbers of people with CF, and knowing who does and does not have CFRD, we identify genetic variations that associate with CFRD. Knowing these variations allows us to better understand the causes of CFRD, and with enough information, better to predict CFRD and identify people at particularly high or low risk of CFRD. People participating in this study also have the option to participate in related studies of other metabolic traits in CF such as over- and underweight.

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。