伤口数据内容比较数据集
提供荷兰和瑞典两个大型伤口队列的对比数据，包括人口统计学和伤口类型，用于预测建模与机器学习。
基本信息
资源简介
伤口数据内容比较数据集
【数据集背景】
本数据集源站标题为《Data content comparison for wound data.》。源站首次发布：2026-01-21。
【数据内容】
源站原始描述：Hard-to-heal wounds are a growing human and financial concern, constituting approximately 1–3% of the healthcare budget. Wound care is not a medical specialty and is often not prioritized within healthcare. A large portion of the cost and suffering caused by wounds has the potential to be mediated through improved knowledge and effectivised workflows. One potential way to achieve this is through the implementation of AI-tools to support clinicians in planning and executing wound care. Informatio…
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 3.xls：application/vnd.ms-excel，5.63 KB。数据集 DOI：10.1371/journal.pone.0339260.t003。
【主题与分类】
源站学科分类：Biophysics、Cell Biology、Biotechnology、Biological Sciences not elsewhere classified、Information Systems not elsewhere classified、Developmental Biology。主题标签：xlink "> hard、discussion section evaluates、2008 &# 8211、care visits conducted、wound related conditions、almost 39000 patients、500 000 patients、one potential way、two wound cohorts、executing wound care。
【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/_p_Data_content_comparison_for_wound_data_p_/31118167
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Gustafsson, Oskar; Lundström, Jens; Ohlsson, Mattias; Stenhamre, Hanna; Tsang, Daniel; Pavia, John; et al. (2026). Data content comparison for wound data.. PLOS ONE. Dataset
下载信息
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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。
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公开数据集受托下载与技术交付服务。
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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：<p>Data content comparison for wound data.</p>
- DOI：10.1371/journal.pone.0339260.t003
- 发布日期：2026-01-21
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/_p_Data_content_comparison_for_wound_data_p_/31118167
命令行下载
curl -L -o "Table 3.xls" "https://ndownloader.figshare.com/files/61200697"
文件清单
Table 3.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
Hard-to-heal wounds are a growing human and financial concern, constituting approximately 1–3% of the healthcare budget. Wound care is not a medical specialty and is often not prioritized within healthcare. A large portion of the cost and suffering caused by wounds has the potential to be mediated through improved knowledge and effectivised workflows. One potential way to achieve this is through the implementation of AI-tools to support clinicians in planning and executing wound care. Information-driven care is a framework for implementing AI-technology in healthcare. Wound Monitor is a Dutch database containing data collected from home-care visits conducted by wound specialists during 2005 to 2022, mostly in Limburg. It contains data of more than 17000 patients. Region Halland, Sweden, created a platform of integrated clinical, financial and operational data called “The Regional Healthcare Information Platform” (RHIP). The platform contains data on over 500 000 patients during 2008–2021. Within this data, a subset of almost 39000 patients have been diagnosed with wounds or wound related conditions. This subset of patients are defined as the RHIP Wound Cohort. This article characterizes the two wound cohorts in terms of demographics and wound types. Further, it examines the quality, quantity and granularity of the respective databases. The discussion section evaluates the strengths and weaknesses of the datasets in terms of the perspective they provide on the patient and wound journey. Lastly, the discussion section also explores how the cohorts may be utilized for predictive modeling and other machine learning-based applications in order to enable information-driven wound care.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0339260.t003（source: https://plos.figshare.com/articles/dataset/_p_Data_content_comparison_for_wound_data_p_/31118167）。
数据缺失？
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