数据集：临床注册元数据作为AI驱动药物发现的隐藏瓶颈：胶质瘤研究中转化阶段数据的计算审计-72907

数据集获取

源站：https://doi.org/10.5281/zenodo.18430432

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。

数据集大小约 4.4 MB。

数据说明

Description This dataset contains raw clinical trial metadata curated for the purpose of computational analysis and audit. The data was retrieved from the WHO International Clinical Trials Registry Platform (ICTRP) to investigate [glioma research] translational trends and data quality. ### Context This record serves as the data foundation for the study: “Clinical registry metadata as a hidden bottleneck in AI-driven drug discovery: a computational audit of translational phase data in glioma research”. The primary objective of providing this dataset is to ensure full transparency, reproducibility, and to allow other researchers to verify the computational findings presented in the associated manuscript. ### Methodology - Data Source: WHO International Clinical Trials Registry Platform (ICTRP) (https://trialsearch.who.int/). - Search Strategy: The dataset was generated using the search term “glioma”. - Date of Extraction: [03.01.2026]. - Data Format: The provided file is in .xlsx format as exported directly from the source portal to maintain data integrity. ### Data Reuse and Reproducibility The analysis of this dataset was performed using a Python-based computational audit. For the source code and step-by-step replication instructions, please refer to the associated GitHub repository: [glioma-metadata-audit]. ### Ethics Statement As this dataset consists of publicly available, de-identified metadata, it does not involve human subjects research. No administrative permissions were required to access this data for research purposes. ### Support the Research If you find this dataset or the associated auditing tools useful, you can support the continuation of this open-science project: - Support my research via PayPal: Direct Donation - Buy Me a Coffee: [irynaoliynyk](buy coffee) Your support helps maintain these open-source tools and supports my ongoing research in neuro-oncology data integrity.

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。