| Full text | |
| Author(s): Show less - |
Clementino Jr, Jose M.
;
Bones, Christian C.
;
Faical, Bruno S.
;
Linares, Oscar C.
;
Lima, Daniel M.
;
Gutierrez, Marco A.
;
Traina Jr, Caetano
;
Traina, Agma J. M.
;
DeHerrera, AGS
;
Gonzalez, AR
;
Santosh, KC
;
Temesgen, Z
;
Kane, B
;
Soda, P
Total Authors: 14
|
| Document type: | Journal article |
| Source: | 2020 IEEE 33RD INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS(CBMS 2020); v. N/A, p. 6-pg., 2020-01-01. |
| Abstract | |
Several studies have been performed worldwide to improve health services using data generated by digital medical systems. The increasing volume of data generated by these systems is making the use of knowledge discovery and data analysis techniques essential to improve the quality of the health services, which are offered by the medical facilities. However, it is possible to observe a gap, in the literature, about generic and flexible vector space models (VSM) that are well adapted to handle electronic health records (EHR), requiring that each knowledge discovery effort develop their own VSM or other representation model. This restriction can turn a knowledge discovery task over clinical pathways nonviable for comparative evaluations among different methods. Targeting such scenario, we propose the Bag-of-Attributes Representation (BOAR). BOAR represents an EHR as an n-dimensional vector space. Since BOAR takes advantage of the OMOP (Observational Medical Outcomes Partnership) standard, BOAR is able to represent records retrieved from different data models. The experimental results show that BOAR is flexible and robust to representing EHR from several sources, and allows the execution and evaluation of several clustering algorithms. (AU) | |
| 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 |
| 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: | 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: | 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: | 18/06074-0 - Recuperação de Imagens por Conteúdo Utilizando Atenção Visual Seletiva |
| Grantee: | Oscar Alonso Cuadros Linares |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |