Automated Mental Disorders Prediction from Textual/Audio Data: A BiLSTM and 2D CNN Approach

dc.contributor.author	Premathilaka, K.K.R.R.
dc.contributor.author	Soyza, E.P.N.
dc.contributor.author	Dissanayaka, H.M.M.K.
dc.contributor.author	Padmasiri, K.M.P.U.
dc.date.accessioned	2026-01-07T10:45:54Z
dc.date.available	2026-01-07T10:45:54Z
dc.date.issued	2024-03-19
dc.identifier.citation	Undergraduates Research Symposium of Faculty of Technology 2024 - (URSoT 2024)	en_US
dc.identifier.issn	2961-5593
dc.identifier.uri	http://repository.rjt.ac.lk/handle/123456789/7959
dc.language.iso	en	en_US
dc.publisher	Faculty of Technology Rajarata University of Sri Lanka	en_US
dc.subject	Automated mental disorders prediction	en_US
dc.subject	Two-dimensional convolutional neural network	en_US
dc.subject	Machine learning	en_US
dc.subject	Suicide and depression	en_US
dc.title	Automated Mental Disorders Prediction from Textual/Audio Data: A BiLSTM and 2D CNN Approach	en_US
dc.type	Article	en_US