2022

M. Bedo, J. S. Ramos, A. Traina, C. Traina Jr., M. Nogueira-Barbosa, Paulo Azevedo-Marques. Wia-Spine: A CBIR environment with embedded radiomic features to assess fragility fractures. 2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS), 72-77. DOI 10.1109/CBMS55023.2022.00020

Aguiar, Julio Erikson, Marcomini, Karem Daiane, Antunes Quirino, Felipe, Gutierrez, Marco A., Traina, Caetano, Traina, Agma J. M. - Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. In: ComputerAided Diagnosis, 2022, San Diego. Medical Imaging 2022: Computer-Aided Diagnosis, 2022. v. 12033. p. 122-128.

Alan Floriano, Igor Eleutério, Caetano Traina Júnior and Agma Juci Machado Traina: Otimização de consultas por similaridade através de técnicas de redução de dimensionalidade, XXIV Congresso Brasileiro de Automação.

Alves, Cézanne, Traina, A.J.M. - Variational Autoencoders for Medical Image Retrieval, in 16th International Conference on Innovations in Intelligent Systems and Applications (INISTA 2022), Biarritz, France, 2022.

Barros, P. H. F. De; and J. F. Rodrigues, AttentionHCare: Advances on computer-aided medical prognosis using attention-based neural networks. IJCNN, 2022, pp. 1-8. DOI: 10.1109/IJCNN55064.2022.9892642.

Bedo, MarcosV.N., Lima, L.L., Koenigkam-Santos, M., Traina, A.J.M., Azevedo-Marques, P.M. - Deep features extracted from Covid-19 and Interstitial Lung Diseases X-Ray images for Content-Based Image Retrieval, Int. J. Computer Assisted Radiology and Surgery (CARS), vol. 17, pp. S13, 2022.

Bedo, M.; J. S. Ramos; A. Traina; C. Traina Jr.; M. Nogueira-Barbosa; Paulo Azevedo-Marques. Wia-Spine: A CBIR environment with embedded radiomic features to assess fragility fractures. 2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS), 72-77. DOI 10.1109/CBMS55023.2022.00020

Carvalho, C. R. R., Chate, R. C., Sawamura, M. V. Y., Garcia, M. L., Lamas, C. A., Cardenas, D. A. C., Lima, D. M., Scudeller, P. G., Salge, J. M., Nomura, C. H., & Gutierrez, M. A. - Chronic lung lesions in COVID-19 survivors: predictive clinical model. BMJ Open, 2022, vol. 12(6), e059110. https://doi.org/10.1136/bmjopen-2021-059110.

CAZZOLATO, Mirela T. ; Traina, Agma J. M. ; BOHM, K. . Establishing trajectories of moving objects without identities: The intricacies of cell tracking and a solution. INFORMATION SYSTEMS, v. 105, p. 101955-69, 2022. https://doi.org/10.1016/j.is.2021.101955.

Cazzolato, Mirela T.; Lucas C. Scabora; Guilherme F. Zabot; Marco A. Gutierrez; Caetano Traina Jr.; Agma J. M. Traina: FeatSet+: Visual Features Extracted from Public Image Datasets. J. Inf. Data Manag. 13(1) (2022). DOI: 10.5753/jidm.2022.2328

Daniela F. Milon-Flores, Robson L.F. Cordeiro: How to take advantage of behavioral features for the early detection of grooming in online conversations. Knowledge-Based Systems, V. 240, p. 108017, 2022, DOI: 10.1016/j.knosys.2021.108017

Gutierrez, M.A., Cardenas, D.A. Cardona, Marcomini, K.D., Traina, A.J.M., Moreno, R.A., Krieger., J.E. - Aplicação da inteligência artificial em imagem cardiovascular: classificação automática de imagens de radiografia de tórax. Revista da Sociedade de Cardiologia do Estado de São Paulo, 2022; vol. 32(1):31-8 http://dx.doi.org/10.29381/0103-8559/2022320131-8.

GUTIERREZ, Marco Antonio; CARDONA CARDENAS, Diego Armando; MARCOMIN, Karem Daiane; MACHADO TRAINA, Agma Juci; MORENO, Ramon Alfredo; KRIEGER, José Eduardo. Aplicação Da Inteligência Artificial em Imagem Cardiovascular: Classificação automática de imagens de radiografia de tórax. REVISTA DA SOCIEDADE DE CARDIOLOGIA DO ESTADO DE SÃO PAULO (SOCESP), v. 32, p. 131-138, 2022. http://dx.doi.org/10.29381/0103-8559/2022320131-8.

Jonathan S. Ramos, Erikson Júlio De Aguiar, Ivar Vargas Belizario, Márcus V. L. Costa, Jamilly G. Maciel, Mirela T. Cazzolato, Caetano Traina, Marcello H. Nogueira-Barbosa, Agma J. M. Traina: Analysis of vertebrae without fracture on spine MRI to assess bone fragility: A Comparison of Traditional Machine Learning and Deep Learning. CBMS 2022: 78-83. DOI: 10.1109/CBMS55023.2022.00021

João Victor de Oliveira Novaes, Lucio Fernandes Dutra Santos, Agma Juci Machado Traina, Caetano Traina Jr.: ORTree: Tuning Diversified Similarity Queries by Means of Data Partitioning. ADBIS 2022: Lecture Notes in Computer Science Vol. 13389, pp. 165-178 DOI: 10.1007/978-3-031-15740-0_13

JÚLIO DE AGUIAR, ERIKSON ; MARCOMINI, KAREM DAIANE ; ANTUNES QUIRINO, FELIPE ; GUTIERREZ, MARCO A. ; TRAINA, CAETANO ; Traina, Agma J. M. . Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. In: ComputerAided Diagnosis, 2022, San Diego. Medical Imaging 2022: Computer-Aided Diagnosis, 2022. v. 1. p. 122-129. https://doi.org/10.1117/12.2611199.

Lima, Lucas L., Koenigkam-Santos, Maurício, Peron, L., Lopes, K.L.F., Lourenço, M.R., Koenigkam-Santos, Marcel, Azevedo-Marques, P.M. - Classifying pulmonary interstitial opacities in chest X-ray images using convolutional neural network and transfer learning, Int. J. Computer Assisted Radiology and Surgery (CARS), vol. 17, pp. S93, 2022.

Lima, D.M., Graves, C.V., Gutierrez, M.A., Brandoli, B., Rodrigues, J.F. (2022): Full Motion Focus: Convolutional Module for Improved Left Ventricle Segmentation Over 4D MRI. Image Analysis and Processing – ICIAP 2022. Lecture Notes in Computer Science, Vol. 13231, p. 438-450. DOI: 10.1007/978-3-031-06427-2_37

Linhares, CLAUDIO D. G. ; LIMA, DANIEL M. ; PONCIANO, JEAN R. ; OLIVATTO, MAURO M. ; GUTIERREZ, MARCO A. ; POCO, JORGE ; TRAINA, CAETANO ; Traina, Agma Juci Machado . ClinicalPath: a Visualization tool to Improve the Evaluation of Electronic Health Records in Clinical Decision-Making. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, v. 1, p. 1-1, 2022. https://doi.org/10.1109/TVCG.2022.3175626.

Linhares, Claudio D. G. ; Jean R. Ponciano; Diogenes S. Pedro; Luis E. C. Rocha; Agma J. M. Traina; Jorge Poco: LargeNetVis: Visual Exploration of Large Temporal Networks Based On Community Taxonomies. IEEE Transactions on Visualization and Computer Graphics, 2022. DOI: 10.1109/TVCG.2022.3209477

MARCOMINI, KAREM D. ; CARDENAS, DIEGO A. C. ; Traina, Agma J. M. ; KRIEGER, JOSÉ E. ; GUTIERREZ, MARCO A. . A deep learning approach for COVID-19 screening and localization on chest x-ray images. In: ComputerAided Diagnosis, 2022, San Diego. Medical Imaging 2022: Computer-Aided Diagnosis, 2022. v. 1. p. 103-112. https://doi.org/10.1117/12.2613177.

Rodrigues, Jose F.; Bailly, Sebastien; Pepin, Jean-louis; Goeuriot, Lorraine; Spadon, Gabriel; Amer-yahia, Sihem; CPAP Adherence Assessment via Gaussian Mixture Modeling of Telemonitored Apnea Therapy. Applied Sciences-Basel, v. 12, p. 7618, 2022. DOI: 10.3390/app12157618

Rodrigues, L. S. ; VESPA, Thiago Galbiatti ; ELEUTERIO, I. A. R. ; OLIVEIRA, W. D. ; Traina, Agma J. M. ; TRAINA JR, Caetano . MiDaS: extract golden results from Knowledge Discovery even over incomplete Databases. In: International Conference on Computational Science (ICCS), 2022, London. Proceedings of the ICCS 2022, 2022. v. 1. p. 1-14. https://doi.org/10.1007/978-3-031-08760-8_54.

Spadon, Gabriel; Shenda Hong; Bruno Brandoli; Stan Matwin; José F. Rodrigues, Jr.; and Jimeng Sun: Pay Attention to Evolution: Time Series Forecasting With Deep Graph-Evolution Learning, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 44, No. 9, pp. 5368-5384. DOI: 10.1109/tpami.2021.3076155

Shuli Jiang, Robson L. F. Cordeiro, Leman Akoglu: D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments. IEEE ICDM'2022, Nov,30-Dec,03 2022.P.1-11. DOI: To be assigned.

2021

J. V. de Oliveira Novaes, L. F. Dutra Santos , L. O. Carvalho , D. de Oliveira, M. V. Naves Bedo, A. J. Machado Traina, C. Traina Jr.: J-EDA: a Workbench to Help Select Parameters in Content-based Image Retrieval, Journal of Information and Data Management - JIDM, pp.1-15. https://doi.org/10.5753/jidm.2021.1990.

G. Spadon, S. Hong, B. Brandoli, S. Matwin, J. F. Rodrigues, J. Sun: Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) , vol. in print, pp. 1-16, 2021. https://doi.org/10.1109/TPAMI.2021.3076155.

F. T. Giuntini, M. T. Cazzolato, K. L. de Moraes, L. de F. Kirchner, M. J. D. dos Reis, Agma J. M. Traina, Andrew T. Campbell, Jó Ueyama: Tracing the emotional roadmap of depressive users on social media through sequential pattern mining, IEEE Access, Vol 9, pp. 97621 - 97635. July 2021. 10.1109/ACCESS.2021.3095759.

F. T. Giuntini, K. L. de Moraes, M. T. Cazzolato, L. de F. Kirchner, M. J. D. dos Reis, Agma J. M. Traina, Andrew T. Campbell, Jó Ueyama - Modeling and assessing the temporal behavior of emotional and depressive user interactions on social networks, IEEE Access, vol 9, pp.93182-93194, June 2021. https://doi.org/10.1109/ACCESS.2021.3091801.

D. M. Lima, J. F. Rodrigues, Jr., B. Brandoli, L. Goeuriot, S. Amer-Yahia: DermaDL: Advanced Convolutional Neural Networks for Computer-Aided Skin-Lesion Classification, Springer Nature Computer Science, vol. 2, pp. 253-265, 2021. https://doi.org/10.1007/s42979-021-00641-5.

D.M. Lima, J.H.G. de Sá, R.A. Moreno, M.S. Rebelo, J.E. Krieger, M.A.Gutierrez. Evaluating the Risk of Covid-19 Infection based on Machine Learning of Symptoms and Conditions versus Laboratory Methods. In: Coleção desafios das engenharias: engenharia de computação 3 / Organizadora Lilian Coelho de Freitas. – Ponta Grossa - PR: Atena, 2021, p. 1-15.

J. Zaghir, J. F. Rodrigues-Jr, L. Goeuriot, S. Amer-Yahia: Real-world Patient Trajectory Prediction from Clinical Notes Using Artificial Neural Networks and UMLS-Based Extraction of Concepts, Journal of Healthcare Informatics Research, 2021. https://doi.org/10.1007/s41666-021-00100-z.

Mirela T. Cazzolato, Lucas Santiago Rodrigues, Marcela Xavier Ribeiro, Marco Antônio Gutierrez, Caetano Traina Jr., Agma Traina - Similarity Search and Correlation-Based Exploratory Analysis in EHRs: A Case Study with COVID-19 Databases, 36 Simpósio Brasileiro de Banco de Dados (SBBD 2021), Virtual, 4-8/10/2021, pp. 1-12. https://doi.org/10.5753/sbbd.2021.17863.

A. T. S. Moriyama, L. S. Rodrigues, L. C. Scabora, M. T. Cazzolato, Agma J. M. Traina, Caetano Traina Jr. - VD-Tree: How to build an efficient and fit metric access method using Voronoi Diagrams, 36th ACM/SIGAPP Symposium on Applied Computing (SAC 2021 - Virtual), Gwangju, South Korea (Virtual), , pp. 327-335. https://doi.org/10.1145/3412841.3441915.

L. C. Scabora, G. Spadon, M. T. Cazzolato, D. Kaster, Agma J. M. Traina, J. F. Rodrigues Jr., Caetano Traina Jr. - SHARq: Sharing Recursive Queries in Relational Databases, 36th ACM/SIGAPP Symposium on Applied Computing (SAC 2021 - Virtual), Gwangju, South Korea (Virtual), pp. 336-339. https://doi.org/10.1145/3412841.3442078.

J. R. Ferreira Jr., M. Koenigkam-Santos, C. V. B. Machado, M. C. Faleiros, N. S. C. Correia, F. E. G. Cipriano, A. T. Fabro, and P. M. d. Azevedo-Marques - Análise radiômica do câncer de pulmão para avaliação prognóstica do paciente e da heterogeneidade intratumoral, Radiologia Brasileira, Vol. 54, No. 2, pp. 87-93. https://doi.org/10.1590/0100-3984.2019.0135.

J. R. Ferreira Jr., M. Koenigkam-Santos, C. d. V. Graves, N. S. C. Correia, F. E. G. Cipriano, A. T. Fabro, and P. M. d. Azevedo-Marques - Quantifying intratumor heterogeneity of lung neoplasms with radiomics, Clinical Imaging, Vol. 74, June 2021, pp. 27-30. https://doi.org/10.1016/j.clinimag.2020.12.017.

Mirela T. Cazzolato; Jonathan S. Ramos; Lucas S. Rodrigues; Lucas C. Scabora; Daniel Y. T. Chino; Ana E. S. Jorge; Paulo Mazzoncini de Azevedo-Marques; Caetano Traina Jr.; Agma J. M. Traina - The UTrack Framework for Segmenting and Measuring Dermatological Ulcers through Telemedicine, Computers in Biology and Medicine, Special Issue in Recent Trends in Cognitive Computing for Healthcare, Volume 134, July 2021, 104489. https://doi.org/10.1016/j.compbiomed.2021.104489.

A. E. A. Jatobá, P. d. Azevedo-Marques, D. Wada, M. Koenigkam-Santos, and M. C. Oliveira - Feasibility study of MRI and multimodality CT/MRI radiomics for lung nodule classification, Intl. Journal of Computer Assisted Radiology and Surgery (CARS) Vol. 16, No. 1, pp. S62-S63. https://doi.org/10.5753/sbcas.2021.16065.

J. S. Ramos, J. Maciel, P. d. Azevedo-Marques, and M. Nogueira-Barbosa - Spine MRI texture analysis and prediction of osteoporotic vertebral fracture, Intl. Journal of Computer Assisted Radiology and Surgery (CARS) Vol. 16, No. 1, pp. S115-S116. https://doi.org/10.1007/s11548-021-02375-4.

Jonathan Ramos, Jamilly Gomes Maciel, Mirela Teixeira Cazzolato, Caetano Traina Jr., Marcello Henrique Nogueira-Barbosa and Agma Traina - BEAUT: a radiomic approach to predict potential lumbar fractures in magnetic resonance imaging, 34th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2021 - Virtual), Aveiro, Portugal, June 7-9, 2021, pp. 389-394. https://doi.ieeecomputersociety.org/10.1109/CBMS52027.2021.00089.

J.R. Ferreira Jr., D.A.C. Cardenas, R.A. Moreno, M.F.S. Rebelo, J.E. Krieger, M.A. Gutierrez - Novel Chest Radiographic Biomarkers for COVID-19 Using Radiomic Features Associated with Diagnostics and Outcomes. Journal of Digital Imaging (2021). https://doi.org/10.1007/s10278-021-00421-w.

J.F. Rodrigues-Jr, M.A. Gutierrez, G. Spadon, B. Brandoli, S. Amer-Yahia - LIG-Doctor: Efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks, Information Sciences, Volume 545, 2021, Pages 813-827, ISSN 0020-0255, https://doi.org/10.1016/j.ins.2020.09.024.

D.A.C. Cardenas, J.F. Ferreira Jr., R.A. Moreno, M.F.S. Rebelo, J.E. Krieger, and M.A. Gutierrez - Automated radiographic bone suppression with deep convolutional neural networks, Proc. SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 116001D (15 February 2021); https://doi.org/10.1117/12.2582210.

C. D. G. Linhares, D. M. Lima, C. C. Bones, M. F. S. Rebelo, M. A. Gutierrez, C. Traina, A. J. M. Traina - I-CovidVis – A Visual Analytics Tool for Interoperable Healthcare Databases using Graphs, 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), 2021, pp. 125-130. https://doi.org/10.1109/CBMS52027.2021.00059.

J. M. Clementino Jr., B. S. Faiçal, C. C. Bones, C. Traina Jr, M. A. Gutierrez, A. J. M. Traina - Multilevel Clustering Explainer: An Explainable Approach to Electronic Health Records, Computer-Based Medical Systems, Online event, 2021, pp. 253-258. https://doi.org/10.1109/CBMS52027.2021.00073.

CAZZOLATO, Mirela T. ; SCABORA, L. C. ; ZABOT, G. ; GUTIERREZ, M. A. ; TRAINA JR, Caetano ; Traina, Agma J. M. . FeatSet: A compilation of Visual Features Extracted From Public Image Datasets. In: Dataset Showcase Workshop (DSW) - SBBD 2021, 2021, Virtual. Anais do Dataset Showcase Workshop (DSW) - SBBD 2021. Porto Alegre: SBC, 2021. v. 1. p. 89-100. https://doi.org/10.5753/dsw.2021.17417.

2020

BLANCO, G.; TRAINA, A.J.M.; TRAINA JR, C.; AZEVEDO-MARQUES, P. M.; JORGE, A. E. S.; OLIVEIRA, D.; BEDO, M. V. N. A superpixel-driven deep learning approach for the analysis of dermatological wounds. Journal on ComputationalMethods and Programs in Biomedicine, Vol. 183, January 2020. 9 pp. https://doi.org/10.1016/j.cmpb.2019.105079.

CHINO, D. Y. T.; SCABORA, L. C.; CAZZOLATO, M. T.; JORGE, A. E. S.;TRAINA JR., C.; TRAINA, A. J. M. Segmenting skin ulcers and measuring the wound area using deep convolutional networks. Journal on Computational Methods and Programs in Biomedicine, Vol. 191. July 2020. 13 pp. https://doi.org/10.1016/j.cmpb.2020.105376.

OLIVEIRA, J. J. M.; CORDEIRO, R. L. F. Unsupervised dimensionality reduction for very large datasets: Are we going to the right direction?. Knowledge-Based Systems, Elsevier, Vol. 196 (2020): 105777, 14 pages. https://doi.org/10.1016/j.knosys.2020.105777.

CAZZOLATO, M. T.; RAMOS, J. S.; RODRIGUES, L. S.; SCABORA, L. C.; CHINO, D. Y. T.; JORGE, A. E. S.; AZEVEDO-MARQUES, P. M., TRAINA JR., C.; TRAINA, A. J. M. Semi-Automatic Ulcer Segmentation and Wound Area Measurement Supporting Telemedicine. IEEE Computer-based Medical Systems (CBMS 2020) July 28–30, 2020, pp. 357- 362. https://doi.org/10.1109/CBMS49503.2020.00073.

RODRIGUES JR., J. F.; BRANDOLI, B.; AMER-YAHIA, S. DermaDL: Advanced Convolutional Neural Networks for automated melanoma detection. IEEE Computer-based Medical Systems (CBMS 2020), July 28-30, 2020, pp. 507-512. https://doi.org/10.1109/CBMS49503.2020.00101.

RODRIGUES JR., J. F.; SPADON, G.; BRANDOLI, B.; AMER-YAHIA, S. Lig-Doctor: Real-world clinical prognosis using a bi-directional neural network, IEEE 33rd International IEEE Computer-based Medical Systems (CBMS 2020), July 28-30, 2020, pp. 572-575. https://doi.org/10.1109/CBMS49503.2020.00113.

FLOREZ, A. Y. C.; SCABORA, L. C.; AMER-YAHIA, S.; RODRIGUES JR., J. F. Augmentation techniques for sequential clinical data to improve Deep Learning prediction techniques. IEEE Computer-based Medical Systems (CBMS 2020), July 28-30, 2020, pp. 600-605. https://doi.ieeecomputersociety.org/10.1109/CBMS49503.2020.00118.

SCABORA, L. C.; SPADON, G.; OLIVEIRA, P. H.; RODRIGUES JR., J. F.; TRAINA JR., C. Enhancing recursive graph querying on RDBMS with data clustering approaches. SAC 2020: pp. 404–411. https://doi.org/10.1145/3341105.3375770.

CABRAL, E. F.; CORDEIRO, R. L. F. Fast and Scalable Outlier Detection with Sorted Hypercubes. ACM International Conference on Information and Knowledge Management - CIKM (2020). 10 pp.https://doi.org/10.1145/3340531.3412033.

RODRIGUES-JR., J. F.; PEPIN, J.; GOEURIOT, L.; AMER-YAHIA, S. An Extensive Investigation of Machine Learning Techniques for Sleep Apnea Screening. ACM International Conference on Information and Knowledge Management (CIKM’20), October 19–23, 2020, Virtual Event, Ireland. 8 pp. https://doi.org/10.1145/3340531.3412686.

RODRIGUES, L. S.; CAZZOLATO, M. T.; TRAINA, A. J. M.; TRAINA JR., C. Taking advantage of highly-correlated attributes in similarity queries with missing values. SISAP Sept. 30-Oct. 2, 2020, 8 pp. https://doi.org/10.1007/978-3-030-60936-8_13.

Ferreira-Junior JR, Koenigkam-Santos M, Magalhães Tenório AP, Faleiros MC, Garcia Cipriano FE, Fabro AT, Näppi J, Yoshida H, de Azevedo-Marques PM. CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms. Int J Comput Assist Radiol Surg. 2020 Jan;15(1):163-172. https://doi.org/10.1007/s11548-019-02093-y.

Tenório APM, Faleiros MC, Junior JRF, Dalto VF, Assad RL, Louzada-Junior P, Yoshida H, Nogueira-Barbosa MH, de Azevedo-Marques PM. A study of MRI-based radiomics biomarkers for sacroiliitis and spondyloarthritis. Int J Comput Assist Radiol Surg. 2020 Jun 30. https://doi.org/10.1007/s11548-020-02219-7.

Faleiros MC, Nogueira-Barbosa MH, Dalto VF, Júnior JRF, Tenório APM, Luppino-Assad R, Louzada-Junior P, Rangayyan RM, de Azevedo-Marques PM. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic 16 resonance imaging. Adv Rheumatol. 2020 May 7;60(1):25. https://doi.org/10.1186/s42358-020-00126-8.

Dorileo, E. A. G. ; Koenigkam-Santos, Marcel ; Fabro, Alexandre Todorovic ; Azevedo-Marques, PM . AI-based radiomic approach in high-resolution CT images for differential diagnosis of idiopathic pulmonary fibrosis. In: CARS 2020 - Computer Assisted Radiology and Surgery, 34th International Congress and Exhibition, 2020, Munich. CARS 2020 - Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23-27, 2020. Int J CARS 15, 1-214 (2020). https://doi.org/10.1007/s11548-020-02171-6, 2020. v. 1. p. 120-121.

Tenório, Ariane Priscilla Magalhães; Faleiros, Matheus Calil; Ferreira-Junior, José Raniery; Dalto, Vitor Faeda; Assad, Rodrigo Luppino; Nogueira-Barbosa, Marcello Henrique; Azevedo-Marques, P.M.: Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences. In: CARS 2020 - Computer Assisted Radiology and Surgery - 34th International Congress and Exhibition, 2020, Munich. CARS 2020 - Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23-27, 2020. Int J CARS 15, 1-214 (2020). https://doi.org/10.1007/s11548-020-02171-6, 2020. v. 1. p. 129-130.

Tenório, Ariane Priscilla Magalhães; Faleiros, Matheus Calil; Ferreira-Junior, José Raniery; Dalto, Vitor Faeda; Assad, Rodrigo Luppino; Nogueira-Barbosa, Marcello Henrique; Azevedo-Marques, P.M.: Radiomic biomarkers for sacroiliitis diagnosis and prediction of spondyloarthritis progression. In: CARS 2020 Computer Assisted Radiology and Surgery - 34th International Congress and Exhibition, 2020, Munich. CARS 2020 - Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23-27, 2020. Int J CARS 15, 1-214 (2020). https://doi.org/10.1007/s11548-020-02171-6, 2020. v. 1. p. 127-129.

Tenório, Ariane Priscilla Magalhães; Faleiros, Matheus Calil; Ferreira-Junior, José Raniery; Dalto, Vitor Faeda; Assad, Rodrigo Luppino; Nogueira-Barbosa, Marcello Henrique; Azevedo-Marques, P.M.: Radiomic biomarkers for sacroiliitis diagnosis and prediction of spondyloarthritis progression. In: CARS 2020 Computer Assisted Radiology and Surgery - 34th International Congress and Exhibition, 2020, Munich. CARS 2020 - Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23-27, 2020. Int J CARS 15, 1-214 (2020). https://doi.org/10.1007/s11548-020-02171-6, 2020. v. 1. p. 127-129.

Lima, Lucas Lins; Ferreira Junior, José Raniery; Fabro, Alexandre Todorovic; Cipriano, Federico Enrique Garcia; Faccio, Adilson; Koenigkam-Santos, Marcel; Azevedo-Marques, PM.: Towards convolutional neural network on primary lung tumors to predict histophatological type, distant and lymph node metastasis. In: CARS 2020 Computer Assisted Radiology and Surgery - the 34th International Congress and Exhibition, 2020, Munich. CARS 2020 - Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23-27, 2020. Int J CARS 15, 1-214 (2020). https://doi.org/10.1007/s11548-020-02171-6, 2020. v. 1. p. 116-117.

Tenorio, A., José Ferreira Jr., J.R., Dalto, V., Faleiros, M., Assad, R., Nogueira-Barbosa, M., Azevedo-Marques, P.M. - Radiomics Assessment of SPAIR and STIR MRI Sequences to Predict Axial and Peripheral Spondyloarthritis, Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS). Porto Alegre (Virtual), Sociedade Brasileira de Computação, 2020, pp. 410-415. https://doi.org/10.5753/sbcas.2020.11532.

Jonathan S. Ramos, Mirela T. Cazzolato, Marcello H. Nogueira-Barbosa, Agma J. M. Traina: FINE: Improving time and precision of segmentation techniques for vertebral compression fractures in MRI. ACM SAC 2020: pp. 198–201. https://doi.org/10.1145/3341105.3374100.

Jonathan S. Ramos, Mirela T. Cazzolato, B.S. Faiçal, O.A.C. Linares, M.H. Nogueira-Barbosa, C. Traina Jr., A.J.M. Traina, "Fast and Smart Segmentation of Paraspinal Muscles in Magnetic Resonance Imaging with CleverSeg", 32nd Conference on Graphics, Patterns and Images (SIBGRAPI 2019). Rio de Janeiro, Brazil: IEEE Computer Society, 2019, pp. 76-83. https://doi.org/10.1109/SIBGRAPI.2019.00019.

Oscar C. Linares, A. Soriano-Vargas, B.S. Faiçal, B. Hamann, A. Fabro, A.J.M. Traina, "Efficient Segmentation of Cell Nuclei in Histopathological Images", IEEE 33rd International IEEE Computer-based Medical Systems (CBMS 2020), vol. 1. Rochester, USA 17 (Virtual): IEEE Computer Society, 2020, pp. 47-52. https://doi.org/10.1109/SIBGRAPI.2019.00019.

J. M. Clementino Jr, C. C. Bones, B. S. Faiçal, O. C. Linares, D. M. Lima, M. A. Gutierrez, C. Traina Jr., A. J. M. Traina. Bag-of-Attributes Representation: A Vector Space Model for Electronic Health Records Analysis in OMOP, 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), Rochester, MN, USA, 2020, pp. 197-202, https://doi.org/10.1109/CBMS49503.2020.00045.

Mirela T. Cazzolato, Jonathan S. Ramos, Lucas S. Rodrigues, Lucas C. Scabora, Daniel Y. T. Chino, Ana E. S. Jorge, Paulo Mazzoncini de Azevedo-Marques, Caetano Traina Jr., Agma J. M. Traina: Semi-Automatic Ulcer Segmentation and Wound Area Measurement Supporting Telemedicine, IEEE Computer-based Medical Systems (CBMS 2020) July 28–30, 2020. https://doi.org/10.1109/CBMS49503.2020.00073.

D.A.C. Cardenas, J.F. Ferreira Jr., R.A. Moreno, M.F.S. Rebelo, J.E. Krieger, and M.A. Gutierrez - Multicenter Validation of Convolutional Neural Networks for Automated Detection of Cardiomegaly on Chest Radiographs. In Anais do XX Simpósio Brasileiro de Computação Aplicada à Saúde, setembro 15, 2020, Evento Online, Brasil. SBC, Porto Alegre, Brasil, 179-190. https://doi.org/10.5753/sbcas.2020.11512.

J. R. Ferreira Jr., D.A.C Cardenas, R. A. Moreno, M.F.S. Rebelo, J.E. Krieger and M.A. Gutierrez - Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images, 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020, pp. 1238-1241, https://doi.org/10.1109/EMBC44109.2020.9176517.

2019

TRAINA, A. J. M.; BRINIS, S.; PEDROSA, G. V.; AVALHAIS, L. P. S.; TRAINA JR., C. Querying on large and complex databases by content: Challenges on variety and veracity regarding real applications. Information Systems 86: PP.10–27 (2019). https://doi.org/10.1016/j.is.2019.03.012.

ZABOT, G. F.; CAZZOLATO, M. T.; SCABORA, L. C.; TRAINA, A. J. M.; TRAINA, C. Efficient Indexing of Multiple Metric Spaces with Spectra. IEEE International Symposium on Multimedia, 2019: pp. 169–176. https://doi.org/10.1109/ISM46123.2019.00038.

CAZZOLATO, M. T.; RODRIGUES, L. S.; SCABORA, L. C.; ZABOT, G. F.; VASCONCELOS, G. Q.; CHINO, D. Y. T.; JORGE, A. E. S.; CORDEIRO, R. L. F.; TRAINA JR., C.; TRAINA, A. J. M. A DBMS-Based Framework for Content-Based Retrival and Analysis of Skin Ulcer Images in Medical Practice. SBBD 2019: pp. 109-120. https://doi.org/10.5753/sbbd.2019.8812.

NOVAIS, J. V. O.; BEDO, M. V. N.; OLIVEIRA, D.; TRAINA, A. TRAINA JR., C.; SANTOS, L. F. D. J-EDA: A diversified similarity workbench for content-based image retrieval. SBBD 2019-Demos and Applications Track Section (Best Demo Paper).

SCABORA, L.; SPADON, G.; RODRIGUES, L.; CAZZOLATO, M.; SOUSA, E.; TRAINA, A. RODRIGUES JR., J.; TRAINA JR., C. G-FranC: A dataset of Criminal Activities mapped as a Complex Network in a Relational DBMS, SBBD 2019-Dataset Show Case, pp. 366–376. (Runner-up Paper).

CAZZOLATO, M. T.; GIUNTINI, F. T.; RUIZ, L. P.; KIRCHNER, L. F.; PASSARELLI, D. A.; REIS, M. J. D.; TRAINA JR., C.; UEYAMA, J. TRAINA, A. J. M. Beyond Tears and Smiles with ReactSet: Records of Users’ Emotions in Facebook Posts. SBBD 2019-Dataset Show Case, pp. 355–365. (Best Paper).

MORAES, L. M. P.; CORDEIRO, R. L. F. SMMnet: A Social Network of Games Dataset. Dataset Showcase Workshop - DSW at the Brazilian Symposium on Databases - SBBD (2019): pp. 429–439.

Santos MK, Ferreira Júnior JR, Wada DT, Tenório APM, Barbosa MHN, Marques PMA. Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine. Radiol Bras. 2019 Nov-Dec;52(6):387-396. https://doi.org/10.1590/0100-3984.2019.0049.

Daniel M. Lima, Jose F. Rodrigues-Jr, Agma J. M. Traina, Fabio A. Pires, Marco A. Gutierrez: Transforming Two Decades of ePR Data to OMOP CDM for Clinical Research, The 17th World Congress of Medical and Health Informatics Studies in Health Technology and Informatics. vol. 264, pp. 233–237, 2019.

Luiz Gustavo S. Real, Renato Bueno, Marcela Xavier Ribeiro: Evaluating Boundary Conditions and Hierarchical Visualization in CBIR, (1) 2019. pp. 68–73. https://doi.org/10.1109/IV.2019.00021.

Claudio Eduardo Paiva, Renato Bueno: Delimitation of Regions of Interest in Similarity Queries Visualization, Information Visualization (1) 2019. pp. 31-36. https://doi.org/10.1109/IV.2019.00015.

TEKLI, J. ; TRAINA, A.J.M. ; TRAINA JR, Caetano ; Chbeir, R. ; YETONGNON, K. ; KALLAS, C. . SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data. KNOWLEDGE-BASED SYSTEMS, v. 164, p. 378-403, 2019. https://doi.org/10.1016/j.knosys.2018.11.010.

CAZZOLATO, Mirela T. ; SCABORA, L. C. ; NESSO JR, M. R. ; MILANO-OLIVEIRA, L. F. ; COSTA, Alceu Ferraz ; Kaster, D. ; SANTOS, M. K. ; Azevedo-Marques, Paulo M. ; 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, 2019. https://doi.org/10.1016/j.cmpb.2019.01.014.

TRAINA JR, Caetano ; CORDEIRO, R. L. F. ; CIFERRI, Cristina ; MORIYAMA, A. T. A. ; ROCHA, G. M. ; TRAINA, AGMA J.M. . The SimilarQL framework: Executing Similarity Queries in Plain SQL. In: 34th ACM/SIGAPP Symposium on Applied Computing (SAC 2019), 2019, Limassol, Cyprus. Proceedings of the 34th Annual ACM Symposium on Applied Computing (SAC 2019) PosterPaper. New York: ACM Press, 2019. v. 1. p. 468-471. https://doi.org/10.1145/3297280.3299736.

RAMOS, JONATHAN S. ; WATANABE, CAROLINA Y. V. ; NOGUEIRA-BARBOSA, MARCELLO H. ; Traina, Agma J. M. . BGrowth. In: the 34th ACM/SIGAPP Symposium, 2019, Limassol. Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing - SAC '19, 2019. v. 1. p. 220-227. https://doi.org/10.1145/3297280.3299728.

ZABOT, G. ; FAICAL, B. S. ; CAZZOLATO, Mirela T. ; SCABORA, L. C. ; Traina, Agma J. M. ; TRAINA JR, Caetano . UCORM: Indexing Uncorrelated Metric Spaces for Concise Content-Based Retrieval of Medical Image. In: 32th IEEE Intl Symposium on Computer-Based Medical Systems (CBMS 2019), 2019, Cordoba. Proceedings of the CBMS2019. Los Alamitos: IEEE Computer Society, 2019. v. 1. p. 1-6. https://doi.org/10.1109/CBMS.2019.00070.

SILVA, W. S. ; JASBICK, D. L. ; ERTHAL, R. ; AZEVEDO-MARQUES, P. M. ; TRAINA, A.J.M. ; SANTOS, L.F.D. ; JORGE, A. E. S. ; OLIVEIRA, D. ; BEDO, M. V. N. . A Two-Phase Learning Approach for the Segmentation of Dermatological Wound. In: 32th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2019), 2019, Cordoba. Proceedings of the IEEE CBMS 2019. Los Alamitos: IEEE Computer Society, 2019. v. 1. p. 1-1. https://doi.org/10.1109/CBMS.2019.00076.

RAMOS, J. S. ; CAZZOLATO, Mirela T. ; FAICAL, B. S. ; NOGUEIRA-BARBOSA, M. H. ; TRAINA, A.J.M. . 3DBGrowth: Volumetric Vertebrae Segmentation and Reconstruction in Magnetic Resonance Imaging. In: 32th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2019), 2019, Cordoba. Proceedings of the CBMS 2019. Los Alamitos: IEEE Computer Society, 2019. v. 1. p. 1-6. https://doi.org/10.1109/CBMS.2019.00091.

LINARES, O. C. ; FAICAL, B. S. ; BARBOSA, P. R. C. ; HAMANN, B. ; FABRO, A. T. ; Traina, Agma J. M. . How to Automatically Identify Regions of Interest in High-resolution Images of Lung Biopsy for Interstitial Fibrosis Diagnosis. In: 32th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2019), 2019, Cordoba. Proceedings of the CBMS 2019 (Poster). Los Alamitos: IEEE Computer Society, 2019. v. 1. p. 1-4. https://doi.org/10.1109/CBMS.2019.00118.

2018

BEDO, M. V. N. ; Kaster, D. ; Traina, Agma J. M. ; TRAINA JR, Caetano . The Merkurion approach for similarity searching optimization in Database Management Systems. DATA & KNOWLEDGE ENGINEERING, v. 113, p. 18-42, 2018. https://doi.org/10.1016/j.datak.2017.09.003.

SCABORA, L. C. ; OLIVEIRA, P. H. ; SOUZA, G. S. ; Kaster, D. ; RODRIGUES JR., José Fernando ; TRAINA, A.J.M. ; TRAINA JR, Caetano . Cutting-edge relational graph data management with Edge-k: From one to multiple edges in the same row. Journal of Information and Data Management - JIDM, v. 9, p. 20-35, 2018. https://periodicos.ufmg.br/index.php/jidm/article/view/413.

Tekli, Joe ; Chbeir, Richard ; TRAINA, AGMA J.M. ; TRAINA, CAETANO ; YETONGNON, KOKOU ; IBANEZ, CARLOS RAYMUNDO ; AL ASSAD, MARC ; KALLAS, CHRISTIAN . Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS. DATA & KNOWLEDGE ENGINEERING, v. 117, p. 133-173, 2018. https://doi.org/10.1016/j.datak.2018.07.007.

BEDO, M. V. N. ; OLIVEIRA, D. ; TRAINA, AGMA J.M. ; TRAINA JR, Caetano . Beyond hit-or-miss: a comparative study of synopses for similarity searching. Journal of Information and Data Management - JIDM, v. 9, p. 36-51, 2018. https://periodicos.ufmg.br/index.php/jidm/article/view/415.

Villela, Karina ; Nass, Claudia ; Novais, Renato ; Simões, Paulo ; Traina, Agma ; Rodrigues, Jose ; Menendez, Jose Manuel ; Kurano, Jorge ; Franke, Tobias ; Poxrucker, Andreas . Reliable and Smart Decision Support System for Emergency Management Based on Crowdsourcing Information. In: Valencia-García R.; Paredes-Valverde M.; Salas-Zárate M.; Alor-Hernández G.. (Org.). Studies in Computational Intelligence. 1ed.Berlin: Springer International Publishing, 2018, v. , p. 177-198. https://doi.org/10.1007/978-3-319-74002-7_9.

SOUZA, Jéssica A. ; Traina, Agma J. M. ; MICHEL, S. . Class-Constraint Similarity Queries. In: 33rd ACM/SIGAPP Symposium on Applied Computing (SAC 2018), 2018, Pau, Nouvelle-Aquitaine. Proceedings of the ACM SAC 2018. New York: ACM, 2018. v. 1. p. 549-556. https://doi.org/10.1145/3167132.3167192

Chino, Daniel Y. T. ; SCABORA, LUCAS C. ; TRAINA, CAETANO ; Traina, Agma J. M. . BoSS. In: the 33rd Annual ACM Symposium, 2018, Pau. Proceedings of the 33rd Annual ACM Symposium on Applied Computing - SAC '18. New York: ACM Press, 2018. v. 1. p. 309-312. https://doi.org/10.1145/3167132.3167374.

NESSO JR, M. R. ; CAZZOLATO, MIRELA TEIXEIRA ; SCABORA, L. C. ; OLIVEIRA, P. H. ; SOUZA, G. S. ; SOUZA, Jéssica A. ; OLIVEIRA, W. D. ; RODRIGUES JR., José Fernando ; Traina, Agma J. M. ; TRAINA JR, Caetano . RAFIKI: Retrieval-Based Application for Imaging and Knowledge Investigation. In: 31st IEEE Intl Symposium on Computer-Based Medical Systems (CBMS 2018), 2018, Karlstad. Proceedings of he CBMS2018. Los Alamitos: IEEE Computer Society, 2018. v. 1. p. 71-76. https://doi.org/10.1109/CBMS.2018.00020.

CHINO, D.Y.T. ; CAZZOLATO, Mirela T. ; SCABORA, L. C. ; TRAINA JR, Caetano ; Traina, Agma J. M. . ICARUS: Retrieving Skin Ulcer Images Through Bag-of-Signatures. In: 31st IEEE Intl. Symposium on Computer-Based Medical Systems (CBMS 2018), 2018, Karlstad. Proceedings of the CBMS 2018. Los Alamitos: IEEE Computer Society, 2018. v. 1. p. 82-87. https://doi.org/10.1109/CBMS.2018.00022.

TEKLI, J. ; Chbeir, R. ; Traina, Agma J. M. ; TRAINA JR, Caetano ; YETONGNON, K. ; IBANEZ, C. R. ; KALLAS, C. . Upgraded SemIndex Prototype supporting Intelligent Database Keyword Queries through Disambiguation, Query As You Type, and Parallel Search Algorithms. In: 2018 IEEE World Congress on Services (IEEE SERVICES 2018), 2018, San Francisco. Proceedings of the IEEE SERVICES 2018. Los Alamitos: IEEE Computer Society, 2018. v. 1. p. 33-40. https://doi.org/10.1109/ICCC.2018.00012.

CAZZOLATO, Mirela T. ; Traina, Agma J. M. ; BOHM, K. . Efficient and Reliable Estimation of Cell Positions. In: 27th ACM International Conference on Information and Knowledge Management (CIKM 2018), 2018, Turin. Proceedings of the 27th CIKM. New York: ACM Press, 2018. v. 1. p. 143-152. https://doi.org/10.1145/3269206.3271734.

2017

SCABORA, L. C. ; OLIVEIRA, P. H. ; Kaster, D. ; TRAINA, A. J. M. ; TRAINA JR, Caetano. Relational graph data management on the edge: Grouping vertices' neighborhood with Edge-k. In: Simpósio Brasileiro de Banco de Dados (SBBD 2017) - Best Paper, 2017, Uberlândia. Anais do SBBD 2017. Porto Alegre: Sociedade Brasileira de Computação, 2017. v. 1. p. 124-135.

BEDO, MARCOS V. N. ; TRAINA JR, Caetano ; TRAINA, A. J. M. A Spline-based Cost Model for Metric Trees. In: Simpósio Brasileiro de Banco de Dados (SBBD 2017), 2017, Uberlândia. Anas do SBBD 2017. Porto Alegre: Sociedade Brasileira de Computação, 2017. v. 1. p. 28-39.

CAZZOLATO, Mirela T. ; AVALHAIS, L. P. S. ; CHINO, D.Y.T. ; RAMOS, J. S. ; SOUZA, Jéssica A. ; RODRIGUES JR., José Fernando ; Traina, Agma J. M. . FiSmo: A Compilation of Datasets from Emergency Situations for Fire and Smoke Analysis. In: SBBD Dataset Showcase Workshop (DSW17), 2017, Uberlândia. Anais do SBBD 2017. Porto Alegre: SBC, 2017. v. 1. p. 1-11.

OLIVEIRA, P. H. ; SCABORA, L. C. ; CAZZOLATO, Mirela T. ; BEDO, M. V. N. ; TRAINA, A. J. M. ; TRAINA JR, Caetano. MAMMOSET: An Enhanced Dataset of Mammograms. In: SBBD Dataset Showcase Workshop (DSW17) - Best Paper, 2017, Uberlândia. Anais do SBBD2017. Porto Alegre: SBC, 2017. v. 1. p. 1-11.