活动性与潜伏性结核全血转录谱（英国测试集）

数据集获取

源站：https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19444

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

This dataset aims to validate and confirm the signature identified in the training set. The aim of the experiment was to define transcriptional signatures in whole blood of TB patients (before drug treatment) and healthy controls to distinguish the signature of Latent and Active TB patients from each other and from healthy controls. This will help in diagnosis of active tuberculosis which normally relies on culture of the bacilli, which can take up to 6 wks, and sometimes the bacilli cannot be obtained from sputum thus requiring invasive techniques obtaining bronchoalveolar lavage (BAL). In some cases the bacill cannot be grown from sputum or BAL. Secondly the aim was to determine whether Latent patients have a homogeneous or heterogeneous signature, one may expect the latter since it is not possible to determine by the present tests (Tuberculin skin test - TST - or MTb antigen responsiveness of blood cells to produce IFN-gamma - IGRA assay) whether the mycobacteria has been cleared, is still present but is controlled, or if patients are recently infected or reactivated and will develop active TB.

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。