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Related papers: Machine Learning for Predicting Epileptic Seizures…

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Refractory epileptic patients can suffer a seizure at any moment. Seizure prediction would substantially improve their lives. In this work, based on scalp EEG and its transformation into images, the likelihood of an epileptic seizure…

Signal Processing · Electrical Eng. & Systems 2022-04-15 Tiago Leal , Fabio Lopes , Cesar Teixeira , Antonio Dourado

Electroencephalogram (EEG) monitoring and objective seizure identification is an essential clinical investigation for some patients with epilepsy. Accurate annotation is done through a time-consuming process by EEG specialists.…

Medical Physics · Physics 2021-04-22 Yikai Yang , Nhan Duy Truong , Christina Maher , Armin Nikpour , Omid Kavehei

Introduction: Machine learning (ML) has been extremely successful in identifying key features from high-dimensional datasets and executing complicated tasks with human expert levels of accuracy or greater. Methods: We summarize and…

Ubiquitous bio-sensing for personalized health monitoring is slowly becoming a reality with the increasing availability of small, diverse, robust, high fidelity sensors. This oncoming flood of data begs the question of how we will extract…

Computer Vision and Pattern Recognition · Computer Science 2017-08-29 JT Turner , Adam Page , Tinoosh Mohsenin , Tim Oates

Sepsis, characterized by a dysregulated immune response to infection, results in significant mortality, morbidity, and healthcare costs. The timely prediction of sepsis progression is crucial for reducing adverse outcomes through early…

Machine Learning · Computer Science 2026-01-01 Alireza Rafiei , Farshid Hajati , Alireza Rezaee , Amirhossien Panahi , Shahadat Uddin

Over the past decade, high-frequency oscillations (HFOs) have been studied as a promising biomarker for localizing epileptogenic areas in drug-resistant patients requiring pre-surgical intervention, while exploiting intracranial…

Signal Processing · Electrical Eng. & Systems 2024-12-24 Zayneb Sadek , Abir Hadriche , Rahma Maalej , Nawel Jmail

Epilepsy is a disorder of the nervous system that can affect people of any age group. With roughly 50 million people worldwide diagnosed with the disorder, it is one of the most common neurological disorders. The EEG is an indispensable…

Populations and Evolution · Quantitative Biology 2022-02-21 Niamh McCallan , Scot Davidson , Kok Yew Ng , Pardis Biglarbeigi , Dewar Finlay , Boon Leong Lan , James McLaughlin

Accurate prediction of epileptic seizures could prove critical for improving patient safety and quality of life in drug-resistant epilepsy. Although deep learning-based approaches have shown promising seizure prediction performance using…

Signal Processing · Electrical Eng. & Systems 2024-12-31 Petros Koutsouvelis , Bartlomiej Chybowski , Alfredo Gonzalez-Sulser , Shima Abdullateef , Javier Escudero

Epilepsy affects millions of people, reducing quality of life and increasing risk of premature death. One-third of epilepsy cases are drug-resistant and require surgery for treatment, which necessitates localizing the seizure onset zone…

Hyperdimensional computing is a promising novel paradigm for low-power embedded machine learning. It has been applied on different biomedical applications, and particularly on epileptic seizure detection. Unfortunately, due to differences…

Signal Processing · Electrical Eng. & Systems 2021-12-20 Una Pale , Tomas Teijeiro , David Atienza

EEG monitoring has an important milestone provide valuable information of those candidates who suffer from epilepsy.In this paper human normal and epileptic Electroencephalogram signals are analyzed with popular and efficient signal…

Computational Engineering, Finance, and Science · Computer Science 2018-02-26 Debadatta Dash

Epileptic seizure detection and classification in clinical electroencephalogram data still is a challenge, and only low sensitivity with a high rate of false positives has been achieved with commercially available seizure detection tools,…

Signal Processing · Electrical Eng. & Systems 2020-07-14 Tomas Iesmantas , Robertas Alzbutas

Epileptic seizures cause abnormal brain activity, and their unpredictability can lead to accidents, underscoring the need for long-term seizure prediction. Although seizures can be predicted by analyzing electroencephalogram (EEG) signals,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Guorui Lu , Jing Peng , Bingyuan Huang , Chang Gao , Todor Stefanov , Yong Hao , Qinyu Chen

Epilepsy is a neurological disorder classified as the second most serious neurological disease known to humanity, after stroke. Localization of the epileptogenic zone is an important step for epileptic patient treatment, which starts with…

Machine Learning (ML) methods have seen widespread adoption in seismology in recent years. The ability of these techniques to efficiently infer the statistical properties of large datasets often provides significant improvements over…

Over the past few decades, electroencephalography (EEG) monitoring has become a pivotal tool for diagnosing neurological disorders, particularly for detecting seizures. Epilepsy, one of the most prevalent neurological diseases worldwide,…

Machine Learning · Computer Science 2025-08-08 Andrea Pollastro , Francesco Isgrò , Roberto Prevete

Epilepsy affects over 50 million people worldwide, and one-third of patients suffer drug-resistant seizures where surgery offers the best chance of seizure freedom. Accurate localization of the epileptogenic zone (EZ) relies on intracranial…

Epilepsy is a common disease of the nervous system. Timely prediction of seizures and intervention treatment can significantly reduce the accidental injury of patients and protect the life and health of patients. This paper presents a…

Signal Processing · Electrical Eng. & Systems 2024-10-01 Qinyu Chen , Congyi Sun , Chang Gao , Shih-Chii Liu

The Epilepsies are a common, chronic neurological disorder affecting more than 50 million individuals across the globe. It is characterized by unprovoked, recurring (similar or different type) seizures which are commonly diagnosed through…

Signal Processing · Electrical Eng. & Systems 2021-08-03 Palak Handa , Monika Mathur , Nidhi Goel

Machine learning has been widely used in healthcare applications to approximate complex models, for clinical diagnosis, prognosis, and treatment. As deep learning has the outstanding ability to extract information from time series, its true…

Machine Learning · Computer Science 2022-11-14 Ke Liao , Wei Wang , Armagan Elibol , Lingzhong Meng , Xu Zhao , Nak Young Chong