Multilevel Clustering Explainer: An Explainable Approach to Electronic Health Records

Author(s):Show less -

Clementino, Jose M., Jr. ; Faical, Bruno S. ; Bones, Christian C. ; Traina, Caetano, Jr. ; Gutierrez, Marco A. ; Traina, Agma J. M. ; Almeida, JR ; Gonzalez, AR ; Shen, L ; Kane, B ; Traina, A ; Soda, P ; Oliveira, JL

• Document type: Journal article
• Source: 2021 IEEE 34TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS); v. N/A, p. 6-pg., 2021-01-01.

Abstract

Machine learning (ML) algorithms have been used in many areas of activity, and their results can often be applied without further human intervention. The ML algorithms have also been widely used in medical contexts, but in this area, the result needs to be thoroughly confirmed by a specialist, who needs explanatory information on how the results were obtained. Aimed at such scenarios, we propose the Multilevel Clustering Explainer (MCE), a method capable of providing explanatory information to health professionals about the knowledge discovery process. The MCE was developed for the analysis of medical data, providing a synthesis of explanatory information for the specialist to quickly and clearly understand how the results were obtained. (AU)

• FAPESP's process: 20/07200-9 - Analyzing complex data from COVID-19 to support decision making and prognosis
• Grantee: Agma Juci Machado Traina
• Support Opportunities: Regular Research Grants
• FAPESP's process: 16/17078-0 - Mining, indexing and visualizing Big Data in clinical decision support systems (MIVisBD)
• Grantee: Agma Juci Machado Traina
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 18/06074-0 - Recuperação de Imagens por Conteúdo Utilizando Atenção Visual Seletiva
• Grantee: Oscar Alonso Cuadros Linares
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 19/04660-1 - Machine Learning Methods Consolidation for MiVisBD
• Grantee: Christian Cesar Bones
• Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training
• FAPESP's process: 18/06228-7 - Detection of patterns and anomalies in medical data using Mathematical Modeling
• Grantee: Bruno Squizato Faiçal
• Support Opportunities: Scholarships in Brazil - Post-Doctoral