囊性纤维化患儿肺功能的机器学习预测
该数据集来源于 clinicaltrials.gov，主题为囊性纤维化（CF）患儿的肺功能机器学习预测。数据为回顾性、横断面、非干预性的二次分析，来自 2021 年 4 月至 2022 年 9 月在 Gazi University 健康科学学院物理治疗与康复系心肺康复单元接受评估的 CF 患儿去标识
基本信息
资源简介
囊性纤维化患儿肺功能的机器学习预测
该数据集来源于 clinicaltrials.gov，主题为囊性纤维化（CF）患儿的肺功能机器学习预测。数据为回顾性、横断面、非干预性的二次分析，来自 2021 年 4 月至 2022 年 9 月在 Gazi University 健康科学学院物理治疗与康复系心肺康复单元接受评估的 CF 患儿去标识化存档数据。源数据来自此前经伦理批准并前瞻性注册（NCT04803643）的观察性研究。该数据可用于构建和评估预测儿童 CF 患者肺功能的机器学习模型（来源 clinicaltrials.gov）。
【数据内容】
源站描述（机器翻译，仅供参考）：条件：囊性纤维化（CF）。本研究是对去标识化存档数据的回顾性、横断面、非干预性二次分析，这些数据来自 2021 年 4 月至 2022 年 9 月期间在 Gazi University 健康科学学院物理治疗与康复系心肺康复单元接受评估的囊性纤维化患儿。源数据是作为此前一项观察性研究的一部分前瞻性收集的，该研究经 Gazi University 伦理委员会批准（决定号 839，2020 年 12 月 7 日），并在 ClinicalTrials.gov 前瞻性注册（NCT04803643）。在源研究中进行评估之前，已获得参与者及其父母或法定监护人的书面知情同意。不会进行新的参与者接触、招募、评估、生物样本采集或干预。
【主题与分类】
主题标签：Cystic Fibrosis (CF)。本站分类：呼吸系统疾病。
【获取与许可】
源站页面：https://clinicaltrials.gov/study/NCT07770854
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
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免登录当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取
源站：https://clinicaltrials.gov/study/NCT07770854
标准获取流程：
- 访问源站链接，注册/登录账号；
- 进入数据集详情页，按页面指引申请权限或直接下载；
- 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。
- OpenDataLab:
数据说明
Conditions: Cystic Fibrosis (CF). This study is a retrospective, cross-sectional, non-interventional secondary analysis of de-identified archived data obtained from children with cystic fibrosis who were evaluated at the Cardiopulmonary Rehabilitation Unit, Department of Physiotherapy and Rehabilitation, Faculty of Health Sciences, Gazi University, between April 2021 and September 2022. The source data were collected prospectively as part of a previous observational study approved by the Gazi University Ethics Commission (Decision No. 839, December 7, 2020) and prospectively registered at ClinicalTrials.gov (NCT04803643). Written informed consent was obtained from the participants and their parents or legal guardians before the assessments conducted in the source study. No new participant contact, recruitment, assessment, biological sample collection, or intervention will be performed for the present secondary analysis. Although the parent study included an age- and sex-matched healthy control group, the present prediction analysis will be restricted to the archived records of 31 children with cystic fibrosis who satisfy the prespecified eligibility criteria and have the variables required for the planned analyses. Pulmonary Function Outcomes Pulmonary function was assessed using a COSMED spirometer (Class II/Internally Powered Equipment, Italy) in accordance with American Thoracic Society/European Respiratory Society standardization criteria. Measurements were performed in the seated position using a nose clip. Participants completed at least three technically acceptable forced expiratory maneuvers, and the highest acceptable values were recorded. Forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF), expressed as both absolute and percent-predicted values, will constitute the prespecified pulmonary function prediction targets. A separate prediction model will be developed for each pulmonary function target. Peripheral Muscle Oxygenation Peripher
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。
需要用于商业化训练或医疗器械注册（NMPA/FDA）？
公开数据往往缺乏完整的病理回证与专家标注。千方医数集依托陕川双基地与超十家三甲医院直连，提供完全合规、去标识化、支持注册级质控的专病数据集交易服务。
