基于最小NPi预测出院结局的受试者工作特征数据
基于最小NPi预测出院结局的ROC数据,包含AUROC和截断点,用于神经重症监护预后研究。

基本信息
资源简介
基于最小NPi预测出院结局的受试者工作特征数据
【数据集背景】
本数据集源站标题为《The receiver operating characteristic data for the prediction of discharge outcome based on minimum NPi》。源站首次发布:2025-05-14。
【数据内容】
源站原始描述:The table presents AUROC values for minimum NPi in predicting discharge outcomes. The optimal cutoff point was determined using Youden’s J statistic, which identifies the threshold that maximizes the combined sensitivity and specificity. Outcome categories are defined as: - Favorable outcome: A change in functional status scale score (FSS) of less than 3 points from admission to discharge- Unfavorable outcome: A change in functional status scale score (FSS) of greater than or equal to 3 points f…
【数据结构与技术规格】
文件数 1 个,合计 17.28 KB。Table 3 Regression analysis.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,17.28 KB。数据集 DOI:10.6084/m9.figshare.29067494.v1。
【主题与分类】
源站学科分类:Medical devices、Intensive care。主题标签:pupillometry、pediatrics、critical care、intensive care、neurological injury。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://figshare.com/articles/dataset/The_receiver_operating_characteristic_data_for_the_prediction_of_discharge_outcome_based_on_minimum_NPi/29067494
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:McGetrick, Molly (2025). The receiver operating characteristic data for the prediction of discharge outcome based on minimum NPi. figshare. Dataset
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
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放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(Figshare)
- 源站标题:The receiver operating characteristic data for the prediction of discharge outcome based on minimum NPi
- DOI:10.6084/m9.figshare.29067494.v1
- 发布日期:2025-05-14
- 文件数:1 个
- 文件总体积:17.28 KB
- 源站页面:https://figshare.com/articles/dataset/The_receiver_operating_characteristic_data_for_the_prediction_of_discharge_outcome_based_on_minimum_NPi/29067494
命令行下载
curl -L -o "Table 3 Regression analysis.docx" "https://ndownloader.figshare.com/files/54545897"
文件清单
Table 3 Regression analysis.docx(17.28 KB)
文件总体积 17.28 KB(源站 API 实测)。
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。
数据说明
The table presents AUROC values for minimum NPi in predicting discharge outcomes. The optimal cutoff point was determined using Youden’s J statistic, which identifies the threshold that maximizes the combined sensitivity and specificity.
Outcome categories are defined as:
- Favorable outcome: A change in functional status scale score (FSS) of less than 3 points from admission to discharge- Unfavorable outcome: A change in functional status scale score (FSS) of greater than or equal to 3 points from admission to discharge- Severe disability: A composite discharge FSS of greater than or equal to 16 points- No severe disability: A composite discharge FSS of less than 16 points- Death: Patient died during hospital admission- Alive: Patient was alive at hospital discharge
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.29067494.v1(source: https://figshare.com/articles/dataset/The_receiver_operating_characteristic_data_for_the_prediction_of_discharge_outcome_based_on_minimum_NPi/29067494)。
数据缺失?
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