LGSPMLOct 6, 2019

Using Deep Learning and Machine Learning to Detect Epileptic Seizure with Electroencephalography (EEG) Data

arXiv:1910.02544v114 citations
Originality Synthesis-oriented
AI Analysis

This work addresses seizure prediction for medical applications, but appears incremental as it builds on existing methods and data without introducing new paradigms.

The paper tackles the challenging problem of epileptic seizure prediction using machine learning on EEG data, aiming to improve forecasting results, but does not report specific numerical outcomes.

The prediction of epileptic seizure has always been extremely challenging in medical domain. However, as the development of computer technology, the application of machine learning introduced new ideas for seizure forecasting. Applying machine learning model onto the predication of epileptic seizure could help us obtain a better result and there have been plenty of scientists who have been doing such works so that there are sufficient medical data provided for researchers to do training of machine learning models.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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