 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: February 2026
Volume 11 | Issue 2
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 117
Article Submitted : 21307
Article Published : 8476
Total Authors : 22301
Total Reviewer : 802
Total Countries : 156
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | A Review of Machine and Deep Learning Techniques in Detecting Suicidal Tendency |
| Authors Name: | Anjana C M |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_186812
|
| Published Paper Id: | IJRTI2305158 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | In recent years, the number of deaths due to suicide has increased. Suicide is becoming one of the major causes of death across the whole world. Early detection and prevention of suicide attempts should be addressed to save people’s life. Thus, several studies found that people who are contemplating suicide can be identified by analyzing social media posts. However, finding and comprehending patterns of suicidal ideation represent a challenging task. The literature has suggested that the detection of suicide thoughts at an early stage can help to rescue the life of people. The idea of early detection has led various researchers to carry out research in this direction. Many such studies have used machine learning and deep learning models to predict the idea of suicide. So, this paper reviews the methods that have been performed towards detection of suicidal thoughts using machine learning and deep learning techniques. |
| Keywords: | Suicides, Suicide Ideation Detection, Machine Learning, Deep Learning |
| Cite Article: | "A Review of Machine and Deep Learning Techniques in Detecting Suicidal Tendency", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.1003 - 1006, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305158.pdf |
| Downloads: | 000205236 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2305158
Registration ID:186812
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: 1003 - 1006 Country: Ernakulam, Kerala, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2305158 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2305158 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||