nanoll extt
Please use this identifier to cite or link to this item: http://lrcdrs.bennett.edu.in:80/handle/123456789/1805
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGoel, Shivani
dc.contributor.authorKapoor, Anika
dc.date.accessioned2023-07-14T12:55:34Z-
dc.date.available2023-07-14T12:55:34Z-
dc.date.issued2022
dc.identifier.urihttps://doi.org/10.1109/IBSSC56953.2022.10037459
dc.identifier.urihttp://lrcdrs.bennett.edu.in:80/handle/123456789/1805-
dc.description.abstractAnxiety disorders have seen an elevating number since the Covid-19 pandemic. This paper aims at identifying more about the various anxiety disorders using machine learning Techniques. Further, symptoms of the types of anxiety disorders: Generalized Anxiety Disorder, Panic Disorder, Post-Traumatic Stress Disorder, Obsessive-Compulsive Disorder and Social Anxiety Disorder are also discussed. The datasets used in the paper are collected by researchers from hospitals/organizations/educational institutions mainly through questionnaires and surveys. Some of the many Machine Learning techniques used for prediction of these anxiety disorders include Random Forest, Linear Regression, Support Vector Machine among others. Lastly, the performance metric for the techniques is presented here and henceforth, the result is drawn from this available data followed by the conclusion. © 2022 IEEE.en_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.titlePrediction of Anxiety Disorders using Machine Learning Techniquesen_US
dc.typeArticleen_US
dc.indexedscen_US
Appears in Collections:Conference/Seminar Papers_ SCSET

Files in This Item:
File SizeFormat 
1783.pdf
  Restricted Access
630.09 kBAdobe PDFView/Open Request a copy

Contact admin for Full-Text

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.