Aljanabi, EhssanTürker, İlker2023-12-222023-12-222022 AğustAljanabi, E., Türker, İ., (2023). EEG-Based Autism Spectrum Disorder Detection: A Bibliometric Analysis. Selcuk University Journal of Engineering Sciences, 22(2), 55-61.https://hdl.handle.net/20.500.12395/51520Autism Spectrum Disorder (ASD) is a common disease in society. Many parents suffer from ignorance of these disorders. Despite the wide prevalence and severity of these disorders, we know little about the neurological basis of the interventions for the purpose of identifying these disorders. One of the popular methods to detect ASD is the Electroencephalography (EEG) signal analysis, thanks to its non-invasive, inexpensive, and accessible nature compared to other neuroimaging technologies. This study contains an overview of detecting ASD with EEG with a bibliometric view driven by the publication statistics provided from the Web of Science database. The analysis includes statistical inferences on the number of publications and received citations in yearly resolution, distribution of document types, research areas, countries, together with the most influential publications, institutions, authors, and journaleninfo:eu-repo/semantics/openAccessAutism detectionAutism Spectrum DisorderAutism Spectrum DisorderDeep learningEEGArticle2225561