Alzahrani, H., & Fernstad, S. (2026). Blurfisheye: A technique for enhanced biological network visualization. In A. Alsadoon, F. Ghareh Mohammadi, F. Shenavarmasouleh, S. Amirian, H. R. Arabnia, & L. Deligiannidis (Eds), Emerging Trends in Computational Biology, Biomedical Engineering, and Health Informatics (Vol. 2935, pp. 82–101). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-22199-5_6
Tag: Sara
Entropy ordered shapes as bivariate glyphs
Holliman, N. S., Çöltekin, A., Fernstad, S. J., McLaughlin, L., Simpson, M. D., & Woods, A. J. (2024). Entropy ordered shapes as bivariate glyphs. Electronic Imaging, 36, 1-10. https://doi.org/10.2352/EI.2024.36.11.HVEI-206
Multi-level visualization for exploration of structures in missing data
Alsufyani, S., Forshaw, M., Del Din, S., Yarnall, A., Rochester, L., & Fernstad, S. J. (2024). Multi-level visualization for exploration of structures in missing data. CGVC. The Eurographics Association.
A Practical Guide to Characterising Data and Investigating Data Quality. University of Leeds
Ruddle, R., Cheshire, J. & Johansson Fernstad, S. (2024). A Practical Guide to Characterising Data and Investigating Data Quality. University of Leeds. https://doi.org/10.5518/1481
An investigation into various visualization tools for complex biological networks
Alzahrani, H. & Johansson Fernstad, S. (2023). An investigation into various visualization tools for complex biological networks. Information Visualization, 22(4), 323-339. https://doi.org/10.1177/14738716231181545
Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases
Romijnders, R., Salis, F., Hansen, C., Küderle, A., Paraschiv-Ionescu, A., Cereatti, A., Alcock, L., Aminian, K., Becker, C., Bertuletti, S., Bonci, T., Brown, P., Buckley, E., Cantu, A., Carsin, A.-E., Caruso, M., Caulfield, B., Chiari, L., D’Ascanio, I., Del Din, S., Eskofier, B., Johansson Fernstad, S., Fröhlich, M. S., Garcia Aymerich, J., Gazit, E., Hausdorff, J. M., Hiden, H., Hume, E., Keogh, A., Kirk, C., Kluge, F., Koch, S., Mazzà, C., Megaritis, D., Micó-Amigo, E., Müller, A., Palmerini, L., Rochester, L., Schwickert, L., Scott, K., Sharrack, B., Singleton, D., Soltani, A., Ullrich, M., Vereijken, B., Vogiatzis, I., Yarnall, A., Schmidt, G., Maetzler, W. (2023). Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases. Frontiers in Neurology, 14, 1247532. https://doi.org/10.3389/fneur.2023.1247532
Tasks and Visualizations Used for Data Profiling: A Survey and Interview Study
Ruddle, R. A., Cheshire, J., & Johansson Fernstad, S. (2023). Tasks and Visualizations Used for Data Profiling: A Survey and Interview Study. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2023.3234337
Parallel Assemblies Plot, a visualization tool to explore categorical and quantitative data: Application to digital mobility outcomes
Cantu, A., Micó-Amigo, M. E., Del Din, S., & Fernstad, S. J. (2023). Parallel Assemblies Plot, a visualization tool to explore categorical and quantitative data: Application to digital mobility outcomes. 2023 IEEE 16th Pacific Visualization Symposium (PacificVis), 21–30. https://doi.org/10.1109/PacificVis56936.2023.00010
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
Micó-Amigo, M. E., Bonci, T., Paraschiv-Ionescu, A., Ullrich, M., Kirk, C., Soltani, A., Küderle, A., Gazit, E., Salis, F., Alcock, L., Aminian, K., Becker, C., Bertuletti, S., Brown, P., Buckley, E., Cantu, A., Carsin, A.-E., Caruso, M., Caulfield, B., Cereatti, A., Chiari, L., D’Ascanio, I., Eskofier, B., Fernstad, S., Froehlich, M., Garcia-Aymerich, J., Hansen, C., Hausdorff, J. M., Hiden, H., Hume, E., Keogh, A., Kluge, F., Koch, S., Maetzler, W., Megaritis, D., Mueller, A., Niessen, M., Palmerini, L., Schwickert, L., Scott, K., Sharrack, B., Sillén, H., Singleton, D., Vereijken, B., Vogiatzis, I., Yarnall, A. J., Rochester, L., Mazzà, C., & Del Din, S. (2023). Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium. Journal of NeuroEngineering and Rehabilitation, 20(1), 78. https://doi.org/10.1186/s12984-023-01198-5
PeaGlyph: Glyph design for investigation of balanced data structures
Koc, K., McGough, A. S., & Johansson Fernstad, S. (2022). PeaGlyph: Glyph design for investigation of balanced data structures. Information Visualization, 21(1), 74-92. https://doi.org/10.1177/14738716211050602
