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Mining, indexing and visualizing Big Data in clinical decision support systems (MIVisBD)

Grant number: 16/17078-0
Support type:Research Projects - Thematic Grants
Duration: September 01, 2017 - February 29, 2024
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal researcher:Agma Juci Machado Traina
Grantee:Agma Juci Machado Traina
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Pesquisadores principais:
Caetano Traina Junior ; Marco Antonio Gutierrez ; Paulo Mazzoncini de Azevedo Marques
Assoc. researchers:André Guilherme Ribeiro Balan ; Christos Faloutsos ; Eneida A. Mendonça ; Fabio Antero Pires ; Joaquim Cezar Felipe ; Joe Tekli ; José Eduardo Krieger ; José Fernando Rodrigues Júnior ; Juan P. Casas ; Marcel Koenigkam Santos ; Marcela Xavier Ribeiro ; Marcello Henrique Nogueira Barbosa ; Marina de Fátima de Sá Rebelo ; Ramon Alfredo Moreno ; Rangaraj Mandayam Rangayyan ; Renato Bueno ; Richard Chbeir ; Robson Leonardo Ferreira Cordeiro ; Sameer Antani ; Solange Oliveira Rezende ; Thomas Martin Deserno ; Umberto Tachinardi
Associated grant(s):21/05623-2 - 25th European Conference on Advances in Databases and Information Systems, AR.EXT
21/06200-8 - 25th International Conference Information Visualisation - IV2021, AR.EXT
20/07200-9 - Analyzing complex data from COVID-19 to support decision making and prognosis, AP.R
+ associated grants 19/20784-2 - III International Clinical Engineering and Health Technology Management Congress (ICEHTMC 2019), AR.EXT
19/06560-4 - 23rd International Conference Information Visualisation, AR.EXT
18/07765-6 - Computational vision and pattern recognition for radionics biomarkers identification, AV.EXT - associated grants
Associated scholarship(s):21/09664-5 - Data integration and interpretability of electronic health records with OMOP, BP.PD
21/06564-0 - Improving the effectiveness of similarity operators in medical data by means of diversity considerations, BP.PD
21/00366-1 - Development of a metric access method with perceptual distance tuning to support similarity queries of medical images, BP.MS
+ associated scholarships 21/02412-0 - Development of a platform for similarity query execution on complex data using multimetric indexing structures, BP.TT
21/00360-3 - Development of software to support similarity queries in healthcare databases, BP.TT
20/12032-8 - Database deployment and machine learning support for radiomics studies, BP.TT
20/11258-2 - Interoperability and similarity queries on medical databases, BP.PD
20/10049-0 - Complex networks and content-based image retrieval supported by selective visual attention features, BP.PD
19/04660-1 - Machine Learning Methods Consolidation for MiVisBD, BP.TT
18/19533-2 - Diagnostic, prognostic, and predictive biomarkers of lung cancer based on radiomics: investigation of deep learning techniques for precision medicine, BP.PD
17/08376-0 - Analysis and improvement of urban systems using digital maps in the form of complex networks, BP.DR
18/24414-2 - A framework for integration of feature extraction techniques and complex databases for MIVisBD, BP.TT
17/23780-2 - Content-based retrieval of medical images to aid the clinical decision using radiomics, BP.DR
18/11424-0 - Creation of a Data Warehouse infrastructure for health-based Visual Analytics, BP.TT
18/06074-0 - Recuperação de Imagens por Conteúdo Utilizando Atenção Visual Seletiva, BP.PD
18/06228-7 - Detection of patterns and anomalies in medical data using Mathematical Modeling, BP.PD
17/24407-3 - Building a database infrastructure to support studies of radiomics, BP.TT
17/21512-0 - Evaluating similarity join algorithms for data streams: case study in the analysis of financial market data, BP.IC - associated scholarships

Abstract

Today, almost every human activity generates and/or demands to store and process massive, diverse and complex data, either in scientific, academic, enterprise and even leisure pursuits - the scenario being called as the “big data era”. Health-related activities are in the core of those activities, as they produce big data as well as they can take advantage of the technological storm, improving the behavior of everyone whose decision is increasingly guided by the information extracted from all these big data. In a clinical environment, the Electronic Health Records (EHR) forms a proper anchor to develop information extraction strategies. In this proposal, we aim at integrating novel database support, image processing and visual analytics methods to leverage the large number of EHR and repositories of clinical data to gather valuable and significant information for decision-making. The size and complexity of EHR databases offer great challenges when they need to be processed in terms both of applying analysis techniques and to support the development of subsequent applications for practical tools. However, it also embodies a cornucopia of opportunities to create algorithms and methods able to display smart and relevant information related to either a particular patient or groups of patients and to boost the EHR into a more effective platform to support the healthcare professionals, coping medical applications and strategic government decisions with the demands and benefits of big data. In this project we will develop methods and algorithms that will ultimately be materialized as a modular platform to be made available to the community. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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VEICULO: TITULO (DATA)

Scientific publications (26)
(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)
LINHARES, CLAUDIO D. G.; PONCIANO, JEAN R.; PAIVA, JOSE GUSTAVO S.; TRAVENCOLO, BRUNO A. N.; ROCHA, LUIS E. C. A comparative analysis for visualizing the temporal evolution of contact networks: a user study. JOURNAL OF VISUALIZATION, v. 24, n. 5, p. 1011-1031, OCT 2021. Web of Science Citations: 0.
CAZZOLATO, MIRELA T.; RAMOS, JONATHAN S.; RODRIGUES, LUCAS S.; SCABORA, LUCAS C.; CHINO, DANIEL Y. T.; JORGE, ANA E. S.; DE AZEVEDO-MARQUES, PAULO MAZZONCINI; JR, CAETANO TRAINA; TRAINA, AGMA J. M. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine. COMPUTERS IN BIOLOGY AND MEDICINE, v. 134, JUL 2021. Web of Science Citations: 0.
BRANDOLI, BRUNO; DE GEUS, ANDRE R.; SOUZA, JEFFERSON R.; SPADON, GABRIEL; SOARES, AMILCAR; RODRIGUES, JR., JOSE F.; KOMOROWSKI, JERZY; MATWIN, STAN. Aircraft Fuselage Corrosion Detection Using Artificial Intelligence. SENSORS, v. 21, n. 12 JUN 2021. Web of Science Citations: 0.
LINHARES, CLAUDIO D. G.; PONCIANO, JEAN R.; PAIVA, JOSE GUSTAVO S.; TRAVENCOLO, BRUNO A. N.; ROCHA, LUIS E. C. A comparative analysis for visualizing the temporal evolution of contact networks: a user study. JOURNAL OF VISUALIZATION, JUN 2021. Web of Science Citations: 0.
ZAGHIR, JAMIL; RODRIGUES-JR, JOSE F.; GOEURIOT, LORRAINE; AMER-YAHIA, SIHEM. Real-world Patient Trajectory Prediction from Clinical Notes Using Artificial Neural Networks and UMLS-Based Extraction of Concepts. JOURNAL OF HEALTHCARE INFORMATICS RESEARCH, JUN 2021. Web of Science Citations: 0.
RODRIGUES-, JR., JOSE F.; GUTIERREZ, MARCO A.; SPADON, GABRIEL; BRANDOLI, BRUNO; AMER-YAHIA, SIHEM. LIG-Doctor: Efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks. INFORMATION SCIENCES, v. 545, p. 813-827, FEB 4 2021. Web of Science Citations: 0.
ALVES, MATHEUS A. C.; CORDEIRO, ROBSON L. F. Effective and unburdensome forecast of highway traffic flow with adaptive computing. KNOWLEDGE-BASED SYSTEMS, v. 212, JAN 5 2021. Web of Science Citations: 0.
GIUNTINI, FELIPE TALIAR; DE MORAES, KAUE L.; CAZZOLATO, MIRELA T.; KIRCHNER, LUZIANE DE FATIMA; DOS REIS, MARIA DE JESUS D.; TRAINA, AGMA J. M.; CAMPBELL, ANDREW T.; UEYAMA, JO. Modeling and Assessing the Temporal Behavior of Emotional and Depressive User Interactions on Social Networks. IEEE ACCESS, v. 9, p. 93182-93194, 2021. Web of Science Citations: 0.
GIUNTINI, FELIPE TALIAR; DE MORAES, KAUE L. P.; CAZZOLATO, MIRELA T.; KIRCHNER, LUZIANE DE FATIMA; DOS REIS, MARIA DE JESUS D.; TRAINA, AGMA J. M.; CAMPBELL, ANDREW T.; UEYAMA, JO. Tracing the Emotional Roadmap of Depressive Users on Social Media Through Sequential Pattern Mining. IEEE ACCESS, v. 9, p. 97621-97635, 2021. Web of Science Citations: 0.
GIUNTINI, FELIPE T.; CAZZOLATO, MIRELA T.; DOS REIS, MARIA DE JESUS DUTRA; CAMPBELL, ANDREW T.; TRAINA, AGMA J. M.; UEYAMA, JO. A review on recognizing depression in social networks: challenges and opportunities. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, v. 11, n. 11, SI, p. 4713-4729, NOV 2020. Web of Science Citations: 7.
SUNDERMANN, CAMILA VACCARI; DE PADUA, RENAN; TONON, VITOR RODRIGUES; MARCACINI, RICARDO MARCONDES; DOMINGUES, MARCOS AURELIO; REZENDE, SOLANGE OLIVEIRA. A context-aware recommender method based on text and opinion mining. EXPERT SYSTEMS, v. 37, n. 6, SI AUG 2020. Web of Science Citations: 3.
CHINO, DANIEL Y. T.; SCABORA, LUCAS C.; CAZZOLATO, MIRELA T.; JORGE, ANA E. S.; TRAINA-, JR., CAETANO; TRAINA, AGMA J. M. Segmenting skin ulcers and measuring the wound area using deep convolutional networks. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, v. 191, JUL 2020. Web of Science Citations: 1.
MAGALHAES TENORIO, ARIANE PRISCILLA; FALEIROS, MATHEUS CALIL; FERREIRA JUNIOR, JOSE RANIERY; DALTO, VITOR FAEDA; ASSAD, RODRIGO LUPPINO; LOUZADA-JUNIOR, PAULO; YOSHIDA, HIROYUKI; NOGUEIRA-BARBOSA, MARCELLO HENRIQUE; DE AZEVEDO-MARQUES, PAULO MAZZONCINI. A study of MRI-based radiomics biomarkers for sacroiliitis and spondyloarthritis. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, v. 15, n. 10 JUN 2020. Web of Science Citations: 0.
MONTEIRO OLIVEIRA, JADSON JOSE; FERREIRA CORDEIRO, ROBSON LEONARDO. Unsupervised dimensionality reduction for very large datasets: Are we going to the right direction?. KNOWLEDGE-BASED SYSTEMS, v. 196, MAY 21 2020. Web of Science Citations: 0.
FALEIROS, MATHEUS CALIL; NOGUEIRA-BARBOSA, MARCELLO HENRIQUE; DALTO, VITOR FAEDA; FERREIRA JUNIOR, JOSE RANIERY; MAGALHAES TENORIO, ARIANE PRISCILLA; LUPPINO-ASSAD, RODRIGO; LOUZADA-JUNIOR, PAULO; RANGAYYAN, RANGARAJ MANDAYAM; DE AZEVEDO-MARQUES, PAULO MAZZONCINI. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. ADVANCES IN RHEUMATOLOGY, v. 60, n. 1 MAY 7 2020. Web of Science Citations: 1.
BLANCO, GUSTAVO; TRAINA, AGMA J. M.; TRAINA JR, CAETANO; AZEVEDO-MARQUES, PAULO M.; JORGE, ANA E. S.; DE OLIVEIRA, DANIEL; BEDO, MARCOS V. N. A superpixel-driven deep learning approach for the analysis of dermatological wounds. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, v. 183, JAN 2020. Web of Science Citations: 2.
GIUNTINI, FELIPE T.; CAZZOLATO, MIRELA T.; DOS REIS, MARIA DE JESUS DUTRA; CAMPBELL, ANDREW T.; TRAINA, AGMA J. M.; UEYAMA, JO. A review on recognizing depression in social networks: challenges and opportunities. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, v. 11, n. 11, SI JAN 2020. Web of Science Citations: 1.
MATHEUS CALIL FALEIROS; MARCELLO HENRIQUE NOGUEIRA-BARBOSA; VITOR FAEDA DALTO; JOSÉ RANIERY FERREIRA JÚNIOR; ARIANE PRISCILLA MAGALHÃES TENÓRIO; RODRIGO LUPPINO-ASSAD; PAULO LOUZADA JUNIOR; RANGARAJ MANDAYAM RANGAYYAN; PAULO MAZZONCINI DE AZEVEDO-MARQUES. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. ADVANCES IN RHEUMATOLOGY, v. 60, p. -, 2020.
BRINIS, SAFIA; TRAINA, JR., CAETANO; TRAINA, AGMA J. M. Hollow-tree: a metric access method for data with missing values. JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, v. 53, n. 3, SI, p. 481-508, DEC 2019. Web of Science Citations: 0.
TRAINA, AGMA J. M.; BRINIS, SAFIA; PEDROSA, V, GLAUCO; AVAIHAIS, LETRICIA P. S.; TRAINA JR, CAETANO. Querying on large and complex databases by content: Challenges on variety and veracity regarding real applications. INFORMATION SYSTEMS, v. 86, p. 10-27, DEC 2019. Web of Science Citations: 0.
FERREIRA-JUNIOR, JOSE RANIERY; KOENIGKAM-SANTOS, MARCEL; MAGALHAES TENORIO, ARIANE PRISCILLA; FALEIROS, MATHEUS CALIL; GARCIA CIPRIANO, FEDERICO ENRIQUE; FABRO, ALEXANDRE TODOROVIC; NAPPI, JANNE; YOSHIDA, HIROYUKI; DE AZEVEDO-MARQUES, PAULO MAZZONCINI. CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, v. 15, n. 1 NOV 2019. Web of Science Citations: 13.
OLIVEIRA, PAULO H.; SCABORA, LUCAS C.; CAZZOLATO, MIRELA T.; OLIVEIRA, WILLIAN D.; PAIXAO, RAFAEL S.; TRAINA, AGMA J. M.; TRAINA, CAETANO. Employing Domain Indexes to Efficiently Query Medical Data From Multiple Repositories. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, v. 23, n. 6, p. 2220-2229, NOV 2019. Web of Science Citations: 1.
SPADON, GABRIEL; DE CARVALHO, ANDRE C. P. L. F.; RODRIGUES-JR, JOSE F.; ALVES, LUIZ G. A. Reconstructing commuters network using machine learning and urban indicators. SCIENTIFIC REPORTS, v. 9, AUG 13 2019. Web of Science Citations: 0.
CAZZOLATO, MIRELA T.; SCABORA, LUCAS C.; NESSO-JR, MARCOS R.; MILANO-OLIVEIRA, LUIS F.; COSTA, ALCEU F.; KASTER, DANIEL S.; KOENIGKAM-SANTOS, MARCEL; DE AZEVEDO-MARQUES, PAULO MAZZONCINI; TRAINA-JR, CAETANO; TRAINA, AGMA J. M. dp-BREATH: Heat maps and probabilistic classification assisting the analysis of abnormal lung regions. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, v. 173, p. 27-34, MAY 2019. Web of Science Citations: 2.
SINOARA, ROBERTA A.; CAMACHO-COLLADOS, JOSE; ROSSI, RAFAEL G.; NAVIGLI, ROBERTO; REZENDE, SOLANGE O. Knowledge-enhanced document embeddings for text classification. KNOWLEDGE-BASED SYSTEMS, v. 163, p. 955-971, JAN 1 2019. Web of Science Citations: 4.
SPADON, GABRIEL; BRANDOLI, BRUNO; ELER, DANILO M.; RODRIGUES-, JR., JOSE F. Detecting multi-scale distance-based inconsistencies in cities through complex-networks. JOURNAL OF COMPUTATIONAL SCIENCE, v. 30, p. 209-222, JAN 2019. Web of Science Citations: 1.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.