Semnatic Enrichment of Medical Information from Networking Complex Heterogeneous

• Grant number: 16/13206-4
• Support Opportunities: Regular Research Grants
• Start date: March 01, 2017
• End date: August 31, 2019
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Alessandra Alaniz Macedo
• Grantee: Alessandra Alaniz Macedo
• Host Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated scholarship(s): 18/02228-2 - Extraction and fusion of biomedical information, BP.TT

Abstract

Multiple information sources, different writing styles, forms of presentation and aspirations by the user (curiosity, decision making, analysis, knowledge, etc.) in relation to information suggest the need to obtain different but similar reports on the same subject. For example, to make decisions health care professionals gather information that vary in terms of media type (text, image and signal), structure (electronic medical records, reports, X-ray images, CT scans, clinical analysis tests, etc.) and content. In this and other examples, information resulting from different media is complementary information and can add semantic value to the understandingof the subject in question. However, for the reading of different information reports to be possible, readers must define search mechanisms, search, select, read and analyze the information provided to them. In addition to demanding a lot of time, such activities cognitively overwhelm readers, who have to devote their attention to the information read, to the path followed, and to mechanisms prepared for this search. This researcher has investigated relationships between information for more one decade, and she is focusing on the use of complex networks to manipulate these relationships. This project proposes the definition of similarity algorithms to create complex heterogeneous networks considering semantic information. We will use biomedical documents such as images, medical records and scientific papers to validate the proposal. We intend to contribute with the reduction of semantic gap between related information. (AU)

Scientific publications

(6)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

NAKAMURA, GILBERTO M.; SOUZA, ALINNE C. C.; SOUZA, FRANCISCO C. M.; BULCAO-NETO, RENATO F.; MARTINEZ, ALEXANDRE S.; MACEDO, ALESSANDRA A.. Using Symmetry to Enhance the Performance of Agent-Based Epidemic Models. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, v. 19, n. 2, p. 10-pg., 2022-03-01. (16/13206-4)

MELONI, FERNANDO; SICCHIERI, BIANCA; MANDRA, PATRICIA; BULCAO-NETO, RENATO; MACEDO, ALESSANDRA ALANIZ; ALMEIDA, JR; GONZALEZ, AR; SHEN, L; KANE, B; TRAINA, A; et al. A Nonverbal Recognition Method to Assist Speech. 2021 IEEE 34TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), v. N/A, p. 6-pg., 2021-01-01. (16/13206-4)

BULCAO-NETO, RENATO F.; NETO, VALDEMAR V. GRACIANO; MACEDO, ALESSANDRA ALANIZ; IEEE. A Reference Architecture for Healthcare Systems with Coded Terminology Support. 2022 INTERMOUNTAIN ENGINEERING, TECHNOLOGY AND COMPUTING (IETC), v. N/A, p. 6-pg., 2022-01-01. (16/13206-4)

MONTEIRO, FLAVIO; MELONI, FERNANDO; BARANAUSKAS, JOSE AUGUSTO; MACEDO, ALESSANDRA ALANIZ. Prediction of mortality in Intensive Care Units: a multivariate feature selection. JOURNAL OF BIOMEDICAL INFORMATICS, v. 107, JUL 2020. (16/13206-4)

MELONI, FERNANDO; SICCHIERI, BIANCA B.; MANDRA, PATRICIA; BULCAO-NETO, RENATO DE FREITAS; MACEDO, ALESSANDRA ALANIZ; IEEE. Detection and Evaluation of Speech Intelligibility with Speech Tool. 2022 XVLIII LATIN AMERICAN COMPUTER CONFERENCE (CLEI 2022), v. N/A, p. 9-pg., 2022-01-01. (16/13206-4)

MACEDO, ALESSANDRA A.; BARANAUSKAS, JOSE A.; BULCAO-NETO, RENATO DE F.; GANZHA, M; MACIASZEK, L; PAPRZYCKI, M. The Evolution of a Healthcare Software Framework: Reuse, Evaluation and Lessons Learned. PROCEEDINGS OF THE 2018 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), v. N/A, p. 9-pg., 2018-01-01. (16/13206-4)