Severity assessment in CDKL5 deficiency disorder

S Demarest, EM Pestana-Knight, HE Olson, J Downs… - Pediatric …, 2019 - Elsevier
Background Pathologic mutations in cyclin-dependent kinase-like 5 cause CDKL5
deficiency disorder, a genetic syndrome associated with severe epilepsy and cognitive …

[HTML][HTML] A review on machine learning approaches in identification of pediatric epilepsy

MIB Ahmed, S Alotaibi, S Dash, M Nabil… - SN Computer …, 2022 - Springer
Epilepsy is the second most common neurological disease after Alzheimer. It is a disorder of
the brain which results in recurrent seizures. Though the epilepsy in general is considered …

Machine learning-based imputation soft computing approach for large missing scale and non-reference data imputation

AH Alamoodi, BB Zaidan, AA Zaidan, OS Albahri… - Chaos, Solitons & …, 2021 - Elsevier
Missing data is a common problem in real-world data sets and it is amongst the most
complex topics in computer science and many other research domains. The common ways …

Flexible realistic simulation of seizure occurrence recapitulating statistical properties of seizure diaries

DM Goldenholz, MB Westover - Epilepsia, 2023 - Wiley Online Library
Objective A realistic seizure diary simulator is currently unavailable for many research
needs, including clinical trial analysis and evaluation of seizure detection and seizure …

Characteristics of large patient‐reported outcomes: where can one million seizures get us?

V Ferastraoaru, DM Goldenholz, S Chiang… - Epilepsia …, 2018 - Wiley Online Library
Objective To analyze data from Seizure Tracker, a large electronic seizure diary, including
comparison of seizure characteristics among different etiologies, temporal patterns in …

Bayesian non-homogeneous hidden Markov model with variable selection for investigating drivers of seizure risk cycling

ET Wang, S Chiang, Z Haneef, VR Rao… - The Annals of Applied …, 2023 - projecteuclid.org
The software implementing our model, with setup instructions and codes replicating the
simulation studies, can be found as online supplement. To request the decryption password …

Individualizing the definition of seizure clusters based on temporal clustering analysis

S Chiang, SR Haut, V Ferastraoaru, VR Rao, MO Baud… - Epilepsy research, 2020 - Elsevier
Objective Seizure clusters are often encountered in people with poorly controlled epilepsy.
Detection of seizure clusters is currently based on simple clinical rules, such as two seizures …

Patterns of epileptic seizure occurrence

M Amengual-Gual, IS Fernández, T Loddenkemper - Brain research, 2019 - Elsevier
Background The occurrence of epileptic seizures in seemingly random patterns takes a
great toll on persons with epilepsy and their families. Seizure prediction may markedly …

Prospective validation study of an epilepsy seizure risk system for outpatient evaluation

S Chiang, DM Goldenholz, R Moss, VR Rao… - …, 2020 - Wiley Online Library
Objective We conducted clinical testing of an automated Bayesian machine learning
algorithm (Epilepsy Seizure Assessment Tool [EpiSAT]) for outpatient seizure risk …

When can we trust responders? Serious concerns when using 50% response rate to assess clinical trials

PJ Karoly, J Romero, MJ Cook, DR Freestone… - …, 2019 - Wiley Online Library
Individual seizure rates are highly volatile, with large fluctuations from month‐to‐month.
Nevertheless, changes in individual mean seizure rates are used to measure whether or not …