生存曲线与置信区间
提供基于PCI模型的心脏植入电子设备生存曲线与置信区间数据,用于比较不同起搏器的电池寿命。

基本信息
资源简介
生存曲线与置信区间
【数据集背景】
本数据集源站标题为《Survival curve and confident intervals.》。源站首次发布:2025-09-29。
【数据内容】
源站原始描述:Aims Generator longevity is the key issue for patients, and is also important for payers, yet implanters of Cardiac Implantable Electronic Devices (CIEDs) face a challenge when selecting the appropriate device since battery longevity is only known for previous generation devices and whilst projected longevities are available for current devices, these are not in comparable formats. This study presents a new framework that facilitates an estimation of longevities for all CIEDs of both previous an…
【数据结构与技术规格】
文件数 1 个,合计 1.66 MB。pone.0333195.s003.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,1.66 MB。数据集 DOI:10.1371/journal.pone.0333195.s003。
【主题与分类】
源站学科分类:Space Science、Medicine、Microbiology、Cell Biology、Molecular Biology、Physiology。主题标签:simple concept entitled、regression analysis showed、novel modelling tool、could simplify personalization、battery capacity allows、battery capacity ).、second largest contributor、certain pacing algorithms、calculated based upon、tailoring device purchases。
【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://plos.figshare.com/articles/dataset/Survival_curve_and_confident_intervals_/30236665
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Defaye, Pascal; Boveda, Serge; Billuart, Jean-Renaud; Witte, Klaus K.; Paton, Maria F. (2025). Survival curve and confident intervals.. PLOS ONE. 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:Survival curve and confident intervals.
- DOI:10.1371/journal.pone.0333195.s003
- 发布日期:2025-09-29
- 文件数:1 个
- 文件总体积:1.66 MB
- 源站页面:https://plos.figshare.com/articles/dataset/Survival_curve_and_confident_intervals_/30236665
命令行下载
curl -L -o "pone.0333195.s003.xlsx" "https://ndownloader.figshare.com/files/58365847"
文件清单
pone.0333195.s003.xlsx(1.66 MB)
文件总体积 1.66 MB(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
Aims
Generator longevity is the key issue for patients, and is also important for payers, yet implanters of Cardiac Implantable Electronic Devices (CIEDs) face a challenge when selecting the appropriate device since battery longevity is only known for previous generation devices and whilst projected longevities are available for current devices, these are not in comparable formats. This study presents a new framework that facilitates an estimation of longevities for all CIEDs of both previous and existing generations that could simplify personalization of the device choice.
Methods
Longevity can be calculated based upon a simple concept entitled the “power consumption index” (PCI = t x I/C, where t is a constant of 1 hour, I is the current required by the device and C, its battery capacity). We retrieved published data from the user manuals of all commonly used pacemakers including single chamber, dual chamber, cardiac resynchronization and leadless devices. C and the components of current I including background current (Ibackground) and the pacing current (Ipacing) were calculated prior to calculation of the PCI for each device. Subsequently, a set of fictitious patient pool conditions via a Monte-Carlo simulation were used to model CIED survival curves which were then compared with real-life data from the Swedish device registry of previous generation CIEDs. Finally, we modeled survival curves for current generation devices using the PCI model.
Results
Using the PCI approach we were able to calculate longevities for all pacemaker devices under a variety of settings. The modeled Ibackground matched the data reported by manufacturers, and, under a variety of settings, regression analysis showed a low average error rate between industry-reported and modelled longevities (ratio: modelled longevity/industry reported longevity −1) = 0.1 ± 4.0% and 0.1 ± 0.7% for previous and existing SR/DR devices, 1.0 ± 5.0% and 0 ± 3.0% for previous and existing CRT-P, and 0 ± 4.0% for leadless pacemakers, respectively).
More than 50% of the PCI and thereby a significant contributor to longevity was accounted for by Ibackground. Ipacing was the second largest contributor (20% for
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0333195.s003(source: https://plos.figshare.com/articles/dataset/Survival_curve_and_confident_intervals_/30236665)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
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