A supervised case-based reasoning approach for explainable thyroid nodule diagnosis

作者：

Highlights：

• A supervised case-based approach (CBR) is proposed for explainable diagnosis of thyroid nodules.

• Both case features and case solutions are considered to determine the similarity between different cases.

• Predictions of unexplainable machine learning models are explained using similar historical cases.

• The proposed approach is compared with traditional CBR approach and mainstream machine learning models.

摘要

•A supervised case-based approach (CBR) is proposed for explainable diagnosis of thyroid nodules.•Both case features and case solutions are considered to determine the similarity between different cases.•Predictions of unexplainable machine learning models are explained using similar historical cases.•The proposed approach is compared with traditional CBR approach and mainstream machine learning models.

论文关键词：Supervised case-based reasoning,Machine learning,Ultrasound,Thyroid nodules,Explainable diagnosis

论文评审过程：Received 4 October 2021, Revised 29 May 2022, Accepted 1 June 2022, Available online 8 June 2022, Version of Record 17 June 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.109200