数据来源：肌张力障碍中酒精反应性的预测因素

数据集获取

源站：https://doi.org/10.5061/dryad.hj08j85

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 167.0 KB。

数据说明

Objective: To determine predictors of alcohol responsiveness in a large cohort of dystonia patients. Methods: 2159 participants with dystonia were prospectively enrolled in the cross-sectional Dystonia Coalition multicenter study. Patients with secondary, combined or confirmed genetic dystonia (total n=164) or unknown alcohol responsiveness (n= 737) were excluded. Patients answered a standardized questionnaire and were clinically examined using a standardized video protocol and the Burke-Fahn-Marsden Dystonia Rating Scale. Alcohol responsiveness was determined by patients’ self-report. Results: 1258 patients with isolated dystonia (mean age: 59.5±12.2 years, female n=898) met the inclusion criteria; 369 patients (29.3%) reported improvement of dystonia after alcohol consumption. Alcohol responsiveness was not related to sex (p = .742), age (p = .715) or severity of dystonia (p = .623). Age at onset was lower in patients who responded to alcohol (p < .001). Alcohol responsiveness differed across dystonia subgroups (multifocal/generalized > segmental (p = .014); cervical and laryngeal > cranial and limb (p < .001)) and was related to a positive family history of movement disorders (p = .001), and presence of tremor (p < .001). Conclusion: The association of alcohol responsiveness with a positive family history for movement disorders, generalized dystonia, and an earlier age at onset suggests that dystonia patients with an underlying genetic contribution may be more likely to respond beneficially to alcohol. The fact that dystonic tremor may respond to alcohol is in keeping with the observation that the intake of GABAergic drugs may have a beneficial effect in a proportion of patients.

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。