规则rk的2×2列联表
用于评估哮喘患者慢性咳嗽相关生活质量的规则rk的2×2列联表，表格数据，支持可解释人工智能分析。
基本信息
资源简介
规则rk的2×2列联表
【数据集背景】
本数据集源站标题为《2 × 2 contingency matrix for rule rk.》。源站首次发布：2024-03-19。
【数据内容】
源站原始描述：Explainable Artificial Intelligence (XAI) is becoming a disruptive trend in healthcare, allowing for transparency and interpretability of autonomous decision-making. In this study, we present an innovative application of a rule-based classification model to identify the main causes of chronic cough-related quality of life (QoL) impairment in a cohort of asthmatic patients. The proposed approach first involves the design of a suitable symptoms questionnaire and the subsequent analyses via XAI. Sp…
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 1.xls：application/vnd.ms-excel，5.63 KB。数据集 DOI：10.1371/journal.pone.0292980.t001。
【主题与分类】
源站学科分类：Cell Biology、Neuroscience、Immunology、Biological Sciences not elsewhere classified、Mathematical Sciences not elsewhere classified、Science Policy。主题标签：may prove helpful、explainable artificial intelligence、based classification model、suitable symptoms questionnaire、main factors influencing、div >< p、life impairment prediction、symptoms associated、main causes、upper airways。
【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/2_2_contingency_matrix_for_rule_i_r_i_sub_i_k_i_sub_/25437357
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Narteni, Sara; Baiardini, Ilaria; Braido, Fulvio; Mongelli, Maurizio (2024). 2 × 2 contingency matrix for rule rk.. PLOS ONE. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：2 × 2 contingency matrix for rule <i>r</i><sub><i>k</i></sub>.
- DOI：10.1371/journal.pone.0292980.t001
- 发布日期：2024-03-19
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/2_2_contingency_matrix_for_rule_i_r_i_sub_i_k_i_sub_/25437357
命令行下载
curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/45136407"
文件清单
Table 1.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
Explainable Artificial Intelligence (XAI) is becoming a disruptive trend in healthcare, allowing for transparency and interpretability of autonomous decision-making. In this study, we present an innovative application of a rule-based classification model to identify the main causes of chronic cough-related quality of life (QoL) impairment in a cohort of asthmatic patients. The proposed approach first involves the design of a suitable symptoms questionnaire and the subsequent analyses via XAI. Specifically, feature ranking, derived from statistically validated decision rules, helped in automatically identifying the main factors influencing an impaired QoL: pharynx/larynx and upper airways when asthma is under control, and asthma itself and digestive trait when asthma is not controlled. Moreover, the obtained if-then rules identified specific thresholds on the symptoms associated to the impaired QoL. These results, by finding priorities among symptoms, may prove helpful in supporting physicians in the choice of the most adequate diagnostic/therapeutic plan.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0292980.t001（source: https://plos.figshare.com/articles/dataset/2_2_contingency_matrix_for_rule_i_r_i_sub_i_k_i_sub_/25437357）。
数据缺失？
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