Amir B. Geva scite author profile

Agreement between manual scorers in a population with moderate sleep-disordered breathing was close to the average pairwise agreement of 87% reported in the Sleep Heart Health Study. The automated classification of sleep stages was also close to this standard. The automated scoring system holds promise as a rapid method to score polysomnographic records, but expert verification of the automated scoring is required.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Amir B. Geva

Unsupervised optimal fuzzy clustering

Autonomic dysregulation in panic disorder and in post-traumatic stress disorder: application of power spectrum analysis of heart rate variability at rest and in response to recollection of trauma or panic attacks

Touch feel illusion in schizophrenic patients

Somatosensory evoked potentials during a rubber-hand illusion in schizophrenia

Assessment of Automated Scoring of Polysomnographic Recordings in a Population with Suspected Sleep-disordered Breathing

Contact Info

Product

Resources

About