阿扎胞苷联合 Lintuzumab 治疗初治骨髓增生异常综合征患者

数据集获取

源站：https://clinicaltrials.gov/study/NCT00997243

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: Leukemia, Myelodysplastic Syndromes. OBJECTIVES: Primary * To determine the complete response rate of the combination of lintuzumab and azacitidine in patients with myelodysplastic syndromes. Secondary * To define the specific toxicities of this regimen. * To determine the overall response rate. * To determine the relationship between pretreatment expression of Syk and clinical response. * To determine whether the investigational agents modulate Syk expression and to correlate drug-induced changes in Syk with response to treatment. * To provide preliminary data on the biological activity of azacitidine as a demethylating agent (changes in target gene methylation and gene expression, DNMT1 protein expression, global methylation). * To perform exploratory studies of azacitidine-triphosphate with global DNA methylation. * To explore the biologic role of microRNA in determining clinical response to this regimen and achievement of the other pharmacodynamic endpoints. OUTLINE: Patients receive azacitidine IV or subcutaneously once daily on days 1-7 and lintuzumab IV on days 2, 7, 15, and 22 (days 2 and 15 of course 1 only). Treatment repeats every 28 days for 6 courses in the absence of disease progression or unacceptable toxicity. Treatment modifications may apply according to response. Blood and bone marrow samples are collected periodically for pharmacodynamic studies. After completion of study treatment, patients are followed up for 5 years.

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。