结构化文献综述结果数据
基于结构化文献综述的放疗中心COVID-19疫情模拟研究数据集,包含21个场景的患者等待时间和吞吐量数据。

基本信息
资源简介
结构化文献综述结果数据
【一句话概览】
本数据集是 figshare 公开的文本数据集,收录 1 个文件、合计 9.73 KB,主题涵盖 simulation study aimed、simulation model demonstrated、maximum waiting times、increased waiting times、external service providers,可用于医学自然语言处理(实体识别、信息抽取等),CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Results from the structured literature review.》。源站首次发布:2025-01-16。
【数据内容】
源站原始描述:Background Radiotherapy practice for cancer treatment is resource-intensive and demands optimised processes for patient throughput while guaranteeing the quality and safety of the therapy. With the COVID-19 pandemic, ad-hoc changes in the operation of radiotherapy centres became necessary to protect patients and staff. This simulation study aimed to quantify the impact of designated COVID-19 protection measures and pandemic-related staff absence on patient waiting times and throughput. The appro…
【数据结构与技术规格】
文件数 1 个,合计 9.73 KB。Table 2.xls:application/vnd.ms-excel,9.73 KB。数据集 DOI:10.1371/journal.pone.0314190.t002。
【主题与分类】
源站学科分类:Biological Sciences not elsewhere classified、Cancer、Science Policy、Infectious Diseases。主题标签:simulation study aimed、simulation model demonstrated、maximum waiting times、increased waiting times、external service providers、demands optimised processes、19 protection tasks、19 incidence rates、two radiation therapists、patient waiting times。
【适用方向】
文本类数据可用于医学自然语言处理,如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/Results_from_the_structured_literature_review_/28221271
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Jambor, Elisabeth; Viana, Joe; Reuter-Oppermann, Melanie; Müller-Polyzou, Ralf (2025). Results from the structured literature review.. 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:Results from the structured literature review.
- DOI:10.1371/journal.pone.0314190.t002
- 发布日期:2025-01-16
- 文件数:1 个
- 文件总体积:9.73 KB
- 源站页面:https://plos.figshare.com/articles/dataset/Results_from_the_structured_literature_review_/28221271
命令行下载
curl -L -o "Table 2.xls" "https://ndownloader.figshare.com/files/51721192"
文件清单
Table 2.xls(9.73 KB)
文件总体积 9.73 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
Background
Radiotherapy practice for cancer treatment is resource-intensive and demands optimised processes for patient throughput while guaranteeing the quality and safety of the therapy. With the COVID-19 pandemic, ad-hoc changes in the operation of radiotherapy centres became necessary to protect patients and staff. This simulation study aimed to quantify the impact of designated COVID-19 protection measures and pandemic-related staff absence on patient waiting times and throughput. The approach also enables analysis of protective measures and process adjustments for future business disruptions.
Methods
A discrete event simulation model of a stand-alone radiotherapy centre was developed and used to analyse changes in patient flow when implementing COVID-19 protection measures and experiencing staff absence. The simulation results support business continuity planning and decision-making in radiotherapy. In total, twenty-one scenarios in three categories were analysed. Category 1 scenarios investigated the effect of healthcare staff and equipment shortfalls. Category 2 scenarios simulated the impact of additional COVID-19 protection measures at low COVID-19 incidence rates, while category 3 scenarios evaluated the changes at high incidence rates.
Results
The simulation results suggested increased patient waiting times when staff is absent. Most scenarios of the three categories behave similarly despite increased patient waiting times due to COVID-19 protection measures in categories 2 and 3. The most significant increase in patient waiting times occurs when only two radiation therapists are available. The absence of a linear accelerator for cancer treatment also leads to increased waiting times. Scenarios where one administrator is absent show the longest average and maximum waiting times for low COVID-19 incidence rates. COVID-19 protection measures reduce patient throughput. In all scenarios, with reduced patient throughput, follow-up radiation appointments were affected.
Conclusions
The simulated scenario results suggest that appropriate staffing of the radiotherapy centre during a pandemic crisis is essential and that staff absence can lead to prolonged pat
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0314190.t002(source: https://plos.figshare.com/articles/dataset/Results_from_the_structured_literature_review_/28221271)。
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。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




