Interactive visual clustering and classification based on dimensionality reduction mappings: A case study for analyzing patients with dermatologic conditions
作者：
Highlights：
• We propose an interactive visualization tool for performing exploratory data analysis.
• The tool combines dimensionality reduction with clustering and classification.
• We conducted different data analysis tasks to demonstrate its use.
• We present a case study using high-dimensional data of dermatologic conditions.
• The analysis suggests that ALA obtains better results than MAL in terms of healing.
摘要
•We propose an interactive visualization tool for performing exploratory data analysis.•The tool combines dimensionality reduction with clustering and classification.•We conducted different data analysis tasks to demonstrate its use.•We present a case study using high-dimensional data of dermatologic conditions.•The analysis suggests that ALA obtains better results than MAL in terms of healing.
论文关键词：Dimensionality reduction,Clustering,Classification,Visual analytics,Dermatology,Photodynamic therapy
论文评审过程：Received 6 November 2019, Revised 5 January 2021, Accepted 11 January 2021, Available online 18 January 2021, Version of Record 5 February 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114605
