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Machine Learning and Deep Learning Techniques for Epileptic Seizures Prediction: A Brief Review

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Practical Applications of Computational Biology and Bioinformatics, 16th International Conference (PACBB 2022) (PACBB 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 553))

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Abstract

The third most common neurological disorder, only behind stroke and migraines, is Epilepsy. The main criteria for its diagnosis are the occurrence of unprovoked seizures and the possibility of new seizures appearing. Usually, the professional in charge of detecting these seizures is a neurologist who interprets the patients’ electroencephalography. However, more accurate, precise, and sensitive methods are needed. Machine learning has increased as a viable alternative, reducing costs and ensuring rapid diagnostic time. This work reviews the state of the art in machine learning applied to epileptic seizure detection and prediction as a prospective study before developing a novel seizure prediction algorithm.

This work was supported by the HERMES project, funded by the European Union under the Horizon 2020 FET-proactive program, Grant Agreement n. 824164., as well as the “XAI - XAI - Sistemas Inteligentes Auto Explicativos creados con Módulos de Mezcla de Expertos” project, ID SA082P20, financed by Junta Castilla y León, Consejería de Educación, and FEDER funds.

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Authors and Affiliations

  1. BISITE Research Group, University of Salamanca, 37007, Salamanca, Spain

    Marco Hernández, Ángel Canal-Alonso, Fernando de la Prieta, Sara Rodríguez, Javier Prieto & Juan Manuel Corchado

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  1. Marco Hernández
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  2. Ángel Canal-Alonso
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  3. Fernando de la Prieta
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  4. Sara Rodríguez
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  5. Javier Prieto
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  6. Juan Manuel Corchado
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Correspondence to Marco Hernández .

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Editors and Affiliations

  1. Computer Science Department, Universidad de Vigo, Vigo, Spain

    Florentino Fdez-Riverola

  2. Campus de Gualtar, Universidade do Minho, Braga, Portugal

    Miguel Rocha

  3. College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates

    Mohd Saberi Mohamad

  4. Gheorghe Asachi Technical University of Iași, Iași, Romania

    Simona Caraiman

  5. Edificio I+D+i, University of Salamanca, Salamanca, Spain

    Ana Belén Gil-González

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Hernández, M., Canal-Alonso, Á., de la Prieta, F., Rodríguez, S., Prieto, J., Corchado, J.M. (2023). Machine Learning and Deep Learning Techniques for Epileptic Seizures Prediction: A Brief Review. In: Fdez-Riverola, F., Rocha, M., Mohamad, M.S., Caraiman, S., Gil-González, A.B. (eds) Practical Applications of Computational Biology and Bioinformatics, 16th International Conference (PACBB 2022). PACBB 2022. Lecture Notes in Networks and Systems, vol 553. Springer, Cham. https://doi.org/10.1007/978-3-031-17024-9_2

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