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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Bou Assi, E., Gagliano, L., Rihana, S., Nguyen, D. K., & Sawan, M. (2018). Bispectrum features and multilayer perceptron classifier to enhance seizure prediction. Scientific Reports, 8(1). Available
Gagliano, L. (2023). Seizure Prediction: From Patient Perspectives to Advanced Signal Processing and Machine Learning Algorithms [Ph.D. thesis, Polytechnique Montréal]. Available
Gagliano, L., Chang, A., Shokooh, L. A., Toffa, D. H., Lesage, F., Sawan, M., Nguyen, D. K., & Bou Assi, E. (2023, July). Cross-bispectrum connectivity of intracranial EEG: A novel approach to seizure onset zone localization [Paper]. 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference (EMBC 2023), Sydney, Australia (4 pages). External link
Gagliano, L., Ding, T. Y., Toffa, D. H., Beauregard, L., Robert, M., Lesage, F., Sawan, M., Nguyen, D. K., & Bou Assi, E. (2023). Decrease in wearable-based nocturnal sleep efficiency precedes epileptic seizures. Frontiers in Neurology, 13, 1089094 (11 pages). External link
Gagliano, L., Bou Assi, E., Herrera-Fortin, T., Lesage, F., Sawan, M., & Nguyen, D. K. (2023). Epileptic Prodromes: Insights from Surveying 196 Patients and 150 Caregivers. Canadian Journal of Neurological Sciences, 50(1), 72-82. External link
Gagliano, L., Lesage, F., Nguyen, D. K., Sawan, M., & Bou Assi, E. (2021, August). Combining bispectral magnitude and entropy measures to improve classification of preictal and ictal iEEG [Paper]. 34th International Epilepsy Congress (1 page). Published in Epilepsia, 62(S3). External link
Gagliano, L., Lesage, F., Bou Assi, E., Nguyen, D. K., & Sawan, M. (2020, June). Neural networks for epileptic seizure prediction: algorithms and hardware implementation [Paper]. 18th IEEE International New Circuits and Systems Conference (NEWCAS 2020), Montréal, Qc, Canada. External link
Gagliano, L., Bou Assi, E., Toffa, D. H., Nguyen, D. K., & Sawan, M. (2020, July). Unsupervised Clustering of HRV Features Reveals Preictal Changes in Human Epilepsy [Paper]. 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 2020), Montréal, QC, Canada. External link
Gagliano, L., Bou Assi, E., Nguyen, D. K., & Sawan, M. (2019). Bispectrum and recurrent neural networks: Improved classification of interictal and preictal states. Scientific Reports, 9(1). Available
Gagliano, L., Bou Assi, E., Sawan, M., & Nguyen, D. K. (2018, October). Bicoherence of intracranial EEG: a novel precursor of seizure activity in canine epilepsy [Paper]. IEEE Life Sciences Conference (LSC 2018), Montréal, Québec. External link
Gagliano, L., Bou Assi, E., Nguyen, D. K., Rihana, S., & Sawan, M. (2018). Bilateral preictal signature of phase-amplitude coupling in canine epilepsy. Epilepsy Research, 139, 123-128. External link
