Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine

作者：

Highlights：

• We propose an automatic detection model of beta-thalassemia carriers based on a hybrid data mining approach.

• A novel and real dataset from Gaza Strip is introduced and studied.

• The highly imbalanced distribution in the dataset is solved by SMOTE oversampling.

• The proposed model will support medical decisions by identifying beta-thalassemia carriers especially in countries with limited recourses or poor health services.

摘要

•We propose an automatic detection model of beta-thalassemia carriers based on a hybrid data mining approach.•A novel and real dataset from Gaza Strip is introduced and studied.•The highly imbalanced distribution in the dataset is solved by SMOTE oversampling.•The proposed model will support medical decisions by identifying beta-thalassemia carriers especially in countries with limited recourses or poor health services.

论文关键词：Thalassemia,Data mining,Classification,SMOTE,Oversampling,Imbalance,Medical dataset

论文评审过程：Received 5 July 2017, Revised 1 December 2017, Accepted 24 April 2018, Available online 3 May 2018, Version of Record 7 June 2018.

论文官网地址：https://doi.org/10.1016/j.artmed.2018.04.009