场景变量数据集

数据集获取（Figshare）

• 源站标题：Scenario variables.
• DOI：10.1371/journal.pone.0314190.t004
• 发布日期：2025-01-16
• 文件数：1 个
• 文件总体积：5.63 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Scenario_variables_/28221277

命令行下载

curl -L -o "Table 4.xls" "https://ndownloader.figshare.com/files/51721198"

文件清单

• Table 4.xls（5.63 KB）

文件总体积 5.63 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.t004（source: https://plos.figshare.com/articles/dataset/Scenario_variables_/28221277）。