基于影像与测序数据的慢性鼻窦炎识别及治疗预后研究

数据集获取

源站：https://clinicaltrials.gov/study/NCT05983003

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: Chronic Sinusitis, Radiology, Pathology, Surgery, Progression. 1. Investigating the heterogeneity of chronic rhinosinusitis: the project will utilize high-throughput information from various sources such as radiology, pathology, and proteomics to gain insights into the multi-dimensional and big data aspects of chronic rhinosinusitis. By analyzing this data, the study aims to identify and understand the different subtypes with more precise and personalized treatment approaches. 2. Developing an intelligent assessment model: using artificial intelligence algorithms, the project will analyze multi-omics data gathered from the research. The goal is to establish an intelligent assessment model that can accurately interpret the data and provide valuable insights into chronic rhinosinusitis. 3. Creating a visual tool for diagnosis and prognosis: the project seeks to integrate multi-omics information to establish an AI model for typing and prognostic prediction. By achieving these research objectives, this project aspires to enhance the understanding of chronic rhinosinusitis and contribute to the development of more precise, personalized, and effective treatment strategies for patients suffering from this condition.

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。