dc.contributor.author |
Abeywickrama, Seniru |
|
dc.date.accessioned |
2024-03-21T09:57:02Z |
|
dc.date.available |
2024-03-21T09:57:02Z |
|
dc.date.issued |
2023 |
|
dc.identifier.citation |
Abeywickrama , Seniru (2023) Depbot - Early Depression Detection from Online Support Forums & Social Networks Using Deep Learning Techniques. BSc. Dissertation, Informatics Institute of Technology |
en_US |
dc.identifier.issn |
2019397 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/1925 |
|
dc.description.abstract |
"Nowadays depression and mental problems are not strange things to us because
normally everyone felt somehow with these symptoms. With the advancement of technology,
there are plenty of treatments, doctors, therapists, and medicines for depression. When
someone had this, divide it into simply three stages mild. moderate and severe. Everyone
should have experienced mild depression because this comes with normal reasons like when
losses someone/something or being angry with someone. This proposed solution will be helpful
for the manual process of depression detection. Currently, psychiatrists and physicians are
using manual methods to identify the symptoms and level of depression but it’s not an ideal
process because of some reasons. This modern society most of the depressed patients are trying
to hide themselves because of social stigma. They won’t admit to get any treatment. The other
reasons are the costly and time-consuming process of depression detection.
Considering the above information, the author targets those people on social
media sites and gives them a better online solution. Severe-stage depression is a very critical
stage for someone trying to suicide themselves. “Dep bot” is a web application that will give
the ability to early detect depression and recommend the best Consultant Psychiatrists and
physicians for the detected results.
The main goal of this system is to design, develop, & evaluate a complementary tool
that can support the day-to-day manual process of early detecting & diagnosed depressive
symptoms, the system finds the symptoms using neural architecture to search for a given
dataset with minimum human involvement." |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
|
en_US |
dc.subject |
Natural Language Processing |
en_US |
dc.subject |
Early Depression Detection |
en_US |
dc.subject |
Data Science |
en_US |
dc.title |
Depbot - Early Depression Detection from Online Support Forums & Social Networks Using Deep Learning Techniques |
en_US |
dc.type |
Thesis |
en_US |