法国重度鼻息肉生物制剂登记研究

数据集获取

源站：https://clinicaltrials.gov/study/NCT06501807

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: Rhinosinusitis Chronic, Nasal Polyps. With a prevalence of 2-4% in western countries, Chronic Rhinosinusitis with Nasal Polyps (CRSwNP) is of major concern regarding its substantial impact on the social and physical quality of life. So far, endoscopic sinus surgery remains the treatment of choice when the first line of medical treatment with corticosteroid has failed. During the last 15 years, several studies have shown that CRSwNP is associated with a T helper 2 (T2) immune response leading to B cell release of IgE, mucosal recruitment of eosinophils from bone marrow via Interleukin (IL)-5, IL-4 and IL-13 mediated chemoattractant production. New biologic agents capable of blocking T2 cytokines have been developed in the field of eosinophil-associated diseases, shifting the paradigm of treatment for patients with CRSwNP. In the near future, endotype profiling with accurate biomarkers will be mandatory to tailor the treatment of nasal polyposis with specific biologic therapies. Herein the investigators propose a prospective study monitoring medical records of CRSwNP patients who undergo biologic treatments. The objectives are to assess treatment efficacy on quality of life, to report clinical and biological criteria for prescription and to measure tolerance and compliance.Patient-reported outcomes will be addressed according to their initial clinical profile (allergy, asthma, NSAID, gastroesophageal reflux disease, obstructive apnea, otologic disorder, smoke habit).

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。