Seizure forecasting using single robust linear feature as correlation vector of seizure-like events in brain slices preparation in vitro
Sign Up to like & getrecommendations! Published in 2019 at "Neurological Research"
DOI: 10.1080/01616412.2018.1532481
Abstract: ABSTRACT Objective: Epilepsy is a neurological disorder affecting 50 million individuals globally. Modern research has inspected the likelihood of forecasting epileptic seizures. Algorithmic investigations are giving promising results for seizure prediction. Though mostly seizure prediction… read more here.
Keywords: seizure forecasting; correlation vector; seizure; feature ... See more keywords
Seizure forecasting using machine learning models trained by seizure diaries
Sign Up to like & getrecommendations! Published in 2022 at "Physiological Measurement"
DOI: 10.1088/1361-6579/aca6ca
Abstract: Objectives. People with refractory epilepsy are overwhelmed by the uncertainty of their next seizures. Accurate prediction of future seizures could greatly improve the quality of life for these patients. New evidence suggests that seizure occurrences… read more here.
Keywords: seizure; machine learning; wise; seizure diaries ... See more keywords
The circadian profile of epilepsy improves seizure forecasting
Sign Up to like & getrecommendations! Published in 2017 at "Brain"
DOI: 10.1093/brain/awx173
Abstract: It is now established that epilepsy is characterized by periodic dynamics that increase seizure likelihood at certain times of day, and which are highly patient-specific. However, these dynamics are not typically incorporated into seizure prediction… read more here.
Keywords: seizure forecasting; epilepsy; prediction algorithms; seizure prediction ... See more keywords
Weak self-supervised learning for seizure forecasting: a feasibility study
Sign Up to like & getrecommendations! Published in 2022 at "Royal Society Open Science"
DOI: 10.1098/rsos.220374
Abstract: This paper proposes an artificial intelligence system that continuously improves over time at event prediction using initially unlabelled data by using self-supervised learning. Time-series data are inherently autocorrelated. By using a detection model to generate… read more here.
Keywords: supervised learning; self supervised; feasibility; feasibility study ... See more keywords
Machine learning from wristband sensor data for wearable, noninvasive seizure forecasting
Sign Up to like & getrecommendations! Published in 2020 at "Epilepsia"
DOI: 10.1111/epi.16719
Abstract: Seizure forecasting may provide patients with timely warnings to adapt their daily activities and help clinicians deliver more objective, personalized treatments. Although recent work has convincingly demonstrated that seizure risk assessment is in principle possible,… read more here.
Keywords: seizure forecasting; sensor data; wristband sensor; machine learning ... See more keywords
Seizure forecasting using minimally-invasive, ultra long-term subcutaneous EEG: (1) Individualized intra-patient models.
Sign Up to like & getrecommendations! Published in 2022 at "Epilepsia"
DOI: 10.1111/epi.17252
Abstract: OBJECTIVE One of the most disabling aspects of living with chronic epilepsy is the unpredictability of seizures. Cumulative research in the past decades has advanced our understanding of the dynamics of seizure risk. Technological advances… read more here.
Keywords: long term; ultra long; term; eeg ... See more keywords
Seizure forecasting using minimally -invasive, ultra long-term subcutaneous EEG: Generalizable cross-patient models.
Sign Up to like & getrecommendations! Published in 2022 at "Epilepsia"
DOI: 10.1111/epi.17265
Abstract: This study describes a generalized cross-patient seizure forecasting approach using recurrent neural networks with ultra long-term subcutaneous EEG (sqEEG) recordings. Data from six patients diagnosed with refractory epilepsy and monitored with a sqEEG device was… read more here.
Keywords: long term; ultra long; cross patient; cross ... See more keywords
Seizure forecasting: bifurcations in the long and winding road.
Sign Up to like & getrecommendations! Published in 2022 at "Epilepsia"
DOI: 10.1111/epi.17311
Abstract: To date the unpredictability of seizures remains a source of suffering for people with epilepsy, motivating decades of research into methods to forecast seizures. Originally, only few scientists and neurologists ventured into this niche endeavor,… read more here.
Keywords: seizure; winding road; long winding; forecasting bifurcations ... See more keywords
Seizure forecasting: Where do we stand?
Sign Up to like & getrecommendations! Published in 2023 at "Epilepsia"
DOI: 10.1111/epi.17546
Abstract: A lot of mileage has been made on the long and winding road towards seizure forecasting recently. Here, we briefly review some selected milestones passed along the way which were discussed at the International Conference… read more here.
Keywords: seizure; forecasting stand; seizure forecasting;
Seizure Forecasting by High-Frequency Activity (80–170 Hz) in Long-term Continuous Intracranial EEG Recordings
Sign Up to like & getrecommendations! Published in 2022 at "Neurology"
DOI: 10.1212/wnl.0000000000200348
Abstract: Background and Objectives Reliable seizure forecasting has important implications in epilepsy treatment and improving the quality of lives for people with epilepsy. High-frequency activity (HFA) is a biomarker that has received significant attention over the… read more here.
Keywords: long term; seizure; hfa; term continuous ... See more keywords
Seizure Forecasting from Idea to Reality. Outcomes of the My Seizure Gauge Epilepsy Innovation Institute Workshop
Sign Up to like & getrecommendations! Published in 2017 at "eNeuro"
DOI: 10.1523/eneuro.0349-17.2017
Abstract: Abstract The Epilepsy Innovation Institute (Ei2) is a new research program of the Epilepsy Foundation designed to be an innovation incubator for epilepsy. Ei2 research areas are selected based on community surveys that ask people… read more here.
Keywords: seizure forecasting; innovation institute; seizure; epilepsy innovation ... See more keywords