Results 241 to 250 of about 15,420 (294)

Smartphone addiction and temporomandibular disorders among university students: A machine learning based multiple regression analysis study. [PDF]

open access: yesMedicine (Baltimore)
Güzel HÇ   +7 more
europepmc   +1 more source

Real world testing and cost‐effectiveness analysis of subcutaneous EEG (REAL‐ASE): Protocol for a prospective multicentre interventional trial

open access: yesEpilepsia Open, EarlyView.
Abstract Objective Epilepsy is a common condition associated with significant morbidity, mortality, and costs. Poor documentation of seizures is a major challenge in epilepsy care. Objective seizure counting with mobile devices may mitigate this challenge and improve patient management.
Matthew McWilliam   +8 more
wiley   +1 more source

How to report neurotechnology and artificial intelligence studies in epilepsy: Peer‐review‐inspired recommendations

open access: yesEpilepsia Open, EarlyView.
Abstract Objective The integration of neurotechnology and artificial intelligence (AI) in epilepsy research has led to significant advancements in diagnosis, monitoring, and treatment. However, the impact of these innovations is often diminished by inadequate and inaccurate reporting, limiting their reproducibility and implementation.
Pedro F. Viana   +6 more
wiley   +1 more source

Smartphone videos for infantile epileptic spasms triaging and assessment (VISTA study): Impact of education and standardized clinical history on diagnostic accuracy

open access: yesEpilepsia Open, EarlyView.
Abstract Objective Diagnostic and treatment delays in infantile epileptic spasms syndrome (IESS) increase the risk of poor neurodevelopmental outcomes. Early clinical recognition of IESS is essential, especially in regions lacking expedited access to electroencephalograms (EEG).
Christine L. Shrock   +11 more
wiley   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

open access: yesEnergy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom   +2 more
wiley   +1 more source

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