确保囊性纤维化患者获得最佳治疗：ENACT 研究

数据集获取

源站：https://clinicaltrials.gov/study/NCT07148739

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 (CF). Understanding variation in genetic response to pharmacological treatments and personalized CFTR modulator response is crucial to the optimization of the use of these novel compounds; expansion to all patients who might benefit from them; and development of predictive biomarkers. In addition, the ability to determine prior to treatment those individuals who will or will not respond to existing therapies will avoid needless risk of side effects and the high cost of a potentially ineffective treatment regimen. Understanding the way these drugs work in the body and the best way to study them and the downstream effects is critical to expanding the use of these drugs to all patients with cystic fibrosis (CF).

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。