评估新型联合治疗方案（D组）与标准治疗用于脓肿分枝杆菌肺病强化期治疗的FORMaT适应性平台试验

数据集获取

源站：https://clinicaltrials.gov/study/NCT07485010

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: Mycobacterium Abscessus Pulmonary Disease, Mycobacterium Abscessus Infection, Non-Tuberculous Mycobacterial (NTM) Infections, Non-Tuberculous Mycobacteria Pulmonary Disease. Mycobacterium abscessus pulmonary disease (MABS-PD) is a rare and serious lung infection that affects people who already have lung problems such as bronchiectasis, cystic fibrosis, past tuberculosis, or weakened immune systems, as well as people who do not have pre-existing lung problems. This infection is becoming more common worldwide and is difficult to treat because it is highly resistant to many antibiotics. Current treatment usually lasts 12-18 months, is hard for patients to tolerate, and often causes significant side effects. This study will test a new combination of antibiotics given during the first four weeks of treatment-the “intensive phase.” The new regimen includes intravenous sulbactam-durlobactam and intravenous ceftriaxone, along with oral amoxicillin, oral azithromycin, and oral clofazimine. The trial will compare this new approach to the current standard-of-care therapy using the existing FORMaT adaptive platform trial, which was created to identify better treatments for MABS-PD. The main goal of the study is to find out whether the new combination can clear the infection while also being easier for patients to tolerate. Additional study measures will look at lung function, chest imaging, quality of life, and health-care use. The trial also includes several research components that will examine how the drugs behave in the body, immune responses, mycobacterial genetics, and antibiotic resistance. This innovative study aims to provide the first high-quality clinical evidence for a potentially more effective and less toxic treatment option for people living with this challenging and severe lung infection.

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。