Results 201 to 210 of about 264,274 (268)

Optimal approach to standardized documentation in epilepsy clinics: A scoping review

Epilepsia, EarlyView.
Abstract Clear documentation and transfer of information between health care providers is key to ensuring the delivery of high‐quality patient care. Our aim was to determine how to optimize and standardize physician documentation in outpatient epilepsy clinics as well as to highlight challenges and barriers to their implementation.
Shahab Marzoughi, Maren Kimura, Bamby Joseph, Alina Zhao, Diane L. Lorenzetti, Dang K. Nguyen, Mark Keezer, Colin B. Josephson, Nathalie Jetté   +8 more
wiley   +1 more source

Accuracy of Medical Image-Based Deep Learning for Detecting Microvascular Invasion in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.

J Med Internet Res
Feng W, Qu B, Han S.
europepmc   +1 more source

Syndrome‐specific and familial imaging traits in juvenile absence epilepsy

Epilepsia, EarlyView.
Abstract Objective Juvenile absence epilepsy (JAE) is an idiopathic generalized epilepsy characterized by absences, generalized tonic–clonic seizures, and cognitive difficulties. In contrast to juvenile myoclonic epilepsy (JME), where distinct functional and structural brain alterations are well established, it remains unclear whether comparable ...
Fenglai Xiao, Lorenzo Caciagli, Luisa Delazer, Sjoerd Vos, Karin Trimmel, Louis Andre Van Graan, Marine Fleury, Lawrence Binding, Davide Giampiccolo, Dominic Heaney, Sanjeev Rajakulendran, Maria Centeno, Josemir W. Sander, John S. Duncan, Matthias J. Koepp, Britta Wandschneider   +15 more
wiley   +1 more source

AI-driven fault detection and classification in photovoltaic systems using deep learning techniques. [PDF]

Sci Rep
Talaat FM, Salem M, Shaban WM.
europepmc   +1 more source

DL-Reg: A deep learning regularization technique using linear regression

Expert Systems with Applications
Maryam Dialameh, Ali Hamzeh, Hossein Rahmani, Safoura Dialameh, Hyock Ju Kwon   +4 more
openaire   +1 more source

Development and validation of a deep survival model to predict time to seizure from routine electroencephalography

Epilepsia, EarlyView.
Abstract Objective This study was undertaken to develop and validate a deep survival model (EEGSurvNet) that analyzes routine electroencephalography (EEG) to predict individual seizure risk over time, comparing its performance to traditional clinical predictors such as interictal epileptiform discharges (IEDs).
Émile Lemoine, An Qi Xu, Mezen Jemel, Frédéric Lesage, Dang K. Nguyen, Elie Bou Assi   +5 more
wiley   +1 more source

Integrating deep learning and radiomics for precise identification of luminal A/B breast cancer subtypes on dynamic contrast-enhanced MRI. [PDF]

Cancer Imaging
Shangguan J, Shchukina E, Monov D, Larina S.   +3 more
europepmc   +1 more source

Ambient technology in epilepsy clinical practice

Epilepsia Open, EarlyView.
Abstract The utilization of large language model‐based artificial intelligence (AI) in the field of neurology has gained attention as a viable tool to enhance and assist providers with processes ranging from scheduling patients to providing preliminary interpretations of testing results, pending orders, and documenting encounters. Epileptologists could
Haania Kakwan, Justin F. Rousseau, Lidia M. Moura, Irfan S. Sheikh   +3 more
wiley   +1 more source