A Prototype for Interactive Information Visualization as Support for Computer-Aided Diagnosis

• Larissa Terto Alvim USP
• Vagner Mendonça Gonçalves USP
• Matheus A. O. Ribeiro USP
• Fátima L. S. Nunes USP

DOI: https://doi.org/10.5753/sbcas_estendido.2025.6990

Resumo

Computer-Aided Diagnosis (CAD) can offer a second opinion to help physicians compose a more precise diagnosis, and interactive Information Visualization (IV) tools can complement CAD systems by providing a more intuitive way to interpret data from patients and exams. In this study, we developed an interactive IV prototype to improve comprehension of a flexible database for a CAD system in the cardiomyopathies context. This prototype is integrated with a web application to retrieve Cardiac Magnetic Resonance exams, and a qualitative evaluation conducted with health professionals showed that IV provided valuable data analysis capability. The results have shown that the integration of advanced visualization tools in our developed prototype can enhance clinical decision-making, improving the effectiveness of CAD systems.

Referências

Alvim, L. T., Gonçalves, V. M., and Nunes, F. L. S. (2025). Building flexible databases by using web services for computer-aided diagnosis of cardiomyopathies: from conceptual definition to evaluation. Submitted and on evaluation process for journal publication.

Bergamasco, L. C. C., Lima, K. R. P. S., Rochitte, C. E., and Nunes, F. L. S. (2022). A bipartite graph approach to retrieve similar 3D models with different resolution and types of cardiomyopathies. Expert Systems with Applications, 193(116422).

Carlisle, S. (2018). Software: Tableau and Microsoft Power BI. Technology | Architecture + Design, 2(2):256–259.

Cheng, L. and Senathirajah, Y. (2023). Using clinical data visualizations in electronic health record user interfaces to enhance medical student diagnostic reasoning: randomized experiment. JMIR Human Factors, 10(e38941).

Costa, S. S. H., Gonçalves, V. M., and Nunes, F. L. S. (2024). Applying ventricular wall shape and motion features from CMRI for aiding diagnosis of cardiomyopathies. In SBC 24th Brazilian Symposium on Computing Applied to Health, pages 142–153.

Federative Republic Brazil (2018). Law no. 13,709 of August 14th, 2018. Available at: [link]. Accessed: Feb. 2nd, 2025. General Law on Personal Data Protection (LGPD).

Gonçalves, V. M., Bergamasco, L. C. C., and Nunes, F. L. S. (2024). 3D Hough Transform-based left ventricle 3D object classification for cardiomyopathy diagnosis. In 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP).

Malik, M. S. A. and Sulaiman, S. (2013). Towards the development of an interface model for information visualization in multiple electronic health records. In 2013 International Conference on Computer Medical Applications (ICCMA).

Mandell, G. A., Keating, M. B., and Khayal, I. S. (2022). Development of a visualization tool for healthcare decision-making using electronic medical records: a systems approach to viewing a patient record. In 2022 IEEE International Systems Conference (SysCon).

Rank, N., Pfahringer, B., Kempfert, J., Stamm, C., Kühne, T., Schoenrath, F., Falk, V., Eickhoff, C., and Meyer, A. (2020). Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance. npj Digital Medicine, 3(139).

Silva, L. S., Aranha, R. V., Ribeiro, M. A. O., Nakamura, R., and Nunes, F. L. S. (2020). Exploring visual attention and machine learning in 3D visualization of medical temporal data. In 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), pages 146–151.

Wang, S., Zhao, Z., Ouyang, X., Wang, Q., and Shen, D. (2024). Interactive computer-aided diagnosis on medical image using large language models. Communications Engineering, 3(133).