Abstract
With the technology industry becoming steadily more and more populated, professionals within the field are finding themselves prone to suffering from different mental health issues. This is accompanied with more willing to share and discuss the issue as well as more resources put available to support sufferers. Bearing the aim to understand better the mental wellbeing of those working in the technological workplace, this paper utilise machine learning techniques to analyse questionnaire survey data acquired from a non-profit corporation of Open Source Mental Illness (OSMI), whereby unsupervised machine learning was used to identify clusters and potential patterns shared between the OSMI respondents; wile artificial neural network was used to analyse whether it’s possible to establish, based on the survey responses, if an individual suffers from mental health problems.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence in Healthcare |
| Editors | Tianhua Chen, Jenny Carter, Mufti Mahmud, Arjab Singh Khuman |
| Publisher | Springer Singapore |
| Chapter | 8 |
| Pages | 165-177 |
| Number of pages | 13 |
| Edition | 1st |
| ISBN (Electronic) | 9789811952722 |
| ISBN (Print) | 9789811952715, 9789811952746 |
| DOIs | |
| Publication status | Published - 26 Oct 2022 |
Publication series
| Name | Brain Informatics and Health |
|---|---|
| Publisher | Springer |
| ISSN (Print) | 2367-1742 |
| ISSN (Electronic) | 2367-1750 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Fingerprint
Dive into the research topics of 'Investigating Mental Wellbeing in the Technology Workplace using Machine Learning Techniques'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver