癌症患者COVID-19管理差分过程挖掘分析数据集
1182名癌症患者COVID-19感染后的治疗路径表格数据，用于过程挖掘分析医院管理差异。
基本信息
资源简介
癌症患者COVID-19管理差分过程挖掘分析数据集
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集，收录 1 个文件、合计 590.01 KB，主题涵盖 process mining、COVID-19、oncology、process analysis、clinical pathways，可用于统计建模、特征工程与队列分析，CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《DataSheet_1_A differential process mining analysis of COVID-19 management for cancer patients.pdf》。配套论文《Clinical Characteristics and Outcomes in Patients with COVID-19 and Cancer: a Systematic Review and Meta-analysis》发表于 Clinical Oncology（2021），DOI：10.1016/j.clon.2020.11.006。源站首次发布：2022-12-07。
【数据内容】
源站原始描述：During the acute phase of the COVID-19 pandemic, hospitals faced a challenge to manage patients, especially those with other comorbidities and medical needs, such as cancer patients. Here, we use Process Mining to analyze real-world therapeutic pathways in a cohort of 1182 cancer patients of the Lausanne University Hospital following COVID-19 infection. The algorithm builds trees representing sequences of coarse-grained events such as Home, Hospitalization, Intensive Care and Death. The same tre…
【数据结构与技术规格】
文件数 1 个，合计 590.01 KB。DataSheet_1_A differential process mining analysis of COVID-19 management for cancer patients.pdf：application/pdf，590.01 KB。数据集 DOI：10.3389/fonc.2022.1043675.s001。
【主题与分类】
源站学科分类：Cancer、Haematological Tumours、Molecular Targets、Radiation Therapy、Oncology and Carcinogenesis not elsewhere classified、Solid Tumours。主题标签：process mining、COVID-19、oncology、process analysis、clinical pathways。
【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://frontiersin.figshare.com/articles/dataset/DataSheet_1_A_differential_process_mining_analysis_of_COVID-19_management_for_cancer_patients_pdf/21686735
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Cuendet, Michel A.; Gatta, Roberto; Wicky, Alexandre; Gerard, Camille L.; Dalla-Vale, Margaux; Tavazzi, Erica; et al. (2022). DataSheet_1_A differential process mining analysis of COVID-19 management for cancer patients.pdf. Frontiers. Dataset
【使用注意】
· 源站最后修改于 2023-06-19，引用时请注意版本时效。
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：DataSheet_1_A differential process mining analysis of COVID-19 management for cancer patients.pdf
- DOI：10.3389/fonc.2022.1043675.s001
- 发布日期：2022-12-07
- 文件数：1 个
- 文件总体积：590.01 KB
- 源站页面：https://frontiersin.figshare.com/articles/dataset/DataSheet_1_A_differential_process_mining_analysis_of_COVID-19_management_for_cancer_patients_pdf/21686735
命令行下载
curl -L -o "DataSheet_1_A differential process mining analysis of COVID-19 management for cancer patients.pdf" "https://ndownloader.figshare.com/files/38459597"
文件清单
DataSheet_1_A differential process mining analysis of COVID-19 management for cancer patients.pdf（590.01 KB）
文件总体积 590.01 KB（源站 API 实测）。
数据说明
During the acute phase of the COVID-19 pandemic, hospitals faced a challenge to manage patients, especially those with other comorbidities and medical needs, such as cancer patients. Here, we use Process Mining to analyze real-world therapeutic pathways in a cohort of 1182 cancer patients of the Lausanne University Hospital following COVID-19 infection. The algorithm builds trees representing sequences of coarse-grained events such as Home, Hospitalization, Intensive Care and Death. The same trees can also show probability of death or time-to-event statistics in each node. We introduce a new tool, called Differential Process Mining, which enables comparison of two patient strata in each node of the tree, in terms of hits and death rate, together with a statistical significance test. We thus compare management of COVID-19 patients with an active cancer in the first vs. second COVID-19 waves to quantify hospital adaptation to the pandemic. We also compare patients having undergone systemic therapy within 1 year to the rest of the cohort to understand the impact of an active cancer and/or its treatment on COVID-19 outcome. This study demonstrates the value of Process Mining to analyze complex event-based real-world data and generate hypotheses on hospital resource management or on clinical patient care.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fonc.2022.1043675.s001（source: https://frontiersin.figshare.com/articles/dataset/DataSheet_1_A_differential_process_mining_analysis_of_COVID-19_management_for_cancer_patients_pdf/21686735）。
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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