基于间皮瘤患者健康记录的诊断预测与特征选择计算数据集

资源简介

基于间皮瘤患者健康记录的诊断预测与特征选择计算数据集

【数据集背景】

本数据集源站标题为《Computational prediction of diagnosis and feature selection on mesothelioma patient health records》。配套论文《Computational prediction of diagnosis and feature selection on mesothelioma patient health records》发表于 PLOS ONE（2019），DOI：10.1371/journal.pone.0208737。源站首次发布：2019-01-10。

【数据内容】

源站原始描述：Background Mesothelioma is a lung cancer that kills thousands of people worldwide annually, especially those with exposure to asbestos. Diagnosis of mesothelioma in patients often requires time-consuming imaging techniques and biopsies. Machine learning can provide for a more effective, cheaper, and faster patient diagnosis and feature selection from clinical data in patient records. Methods and findings We analyzed a dataset of health records of 324 patients having mesothelioma symptoms from Tu…

【数据结构与技术规格】

文件数 10 个，合计 73.73 MB。pone.0208737.s001.pdf：application/pdf，115.19 KB。数据集 DOI：10.1371/journal.pone.0208737。

【主题与分类】

源站学科分类：Medicine、Cell Biology、Genetics、Biotechnology、Biological Sciences not elsewhere classified、Information Systems not elsewhere classified。主题标签：decision tree classifiers、mesothelioma patient health records Background Mesothelioma、forest feature selection、patient records、dataset diagnosis prediction、Matthews correlation coefficient、feature selection、lung side、decision tree、mesothelioma symptoms。

【适用方向】

源站学科分类标注为 Medicine、Cell Biology、Genetics、Biotechnology、Biological Sciences not elsewhere classified、Information Systems not elsewhere classified。

【获取与许可】

源站页面：https://plos.figshare.com/articles/dataset/Computational_prediction_of_diagnosis_and_feature_selection_on_mesothelioma_patient_health_records/7573019

使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。

规范引用：Chicco, Davide; Rovelli, Cristina (2019). Computational prediction of diagnosis and feature selection on mesothelioma patient health records. PLOS ONE. Dataset

【使用注意】

· 源站最后修改于 2023-06-04，引用时请注意版本时效。