肺冷凝物：哮喘与囊性纤维化肺部受累的无创评估

数据集获取

源站：https://clinicaltrials.gov/study/NCT04157361

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: Bronchial Asthma, Pulmonary Cystic Fibrosis. Exhaled breath condensate (EBC) represents a rich source for countless biomarkers that can provide valuable information about respiratory as well as systemic diseases. Finding non-invasive methods for early detection of lung injury, inflammation and infectious complications in chronic diseases like Cystic fibrosis (CF) or Bronchial asthma (AB) would be highly beneficial. Investigators propose to establish EBC “breathprints” revealing molecular signatures of pulmonary inflammation and specific respiratory bacterial infections of CF patients and AB. Investigators hypothesize that the analysis of EBC can reveal biomarkers specific for severity of the inflammation, and infection caused by opportunistic pathogens such as P. aeruginosa (PA). With these breath-prints, investigators also propose to establish correlations between respiratory microbiota using traditional methods and CF lung disease severity. Together, the studies will advance the development and validation of EBC as a novel tool for the proper diagnosis of AB and monitoring of CF disease activity, treatment efficacy and PA or another opportunistic infections.

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。