Single classifer vs. ensemble machine learning approaches for mental health prediction
Early prediction of mental health issues among individuals is paramount for early diagnosis and treatment by mental health professionals. One of the promising approaches to achieving fully automated computer-based approaches for predicting mental health problems is via machine learning. As such, thi...
Main Authors: | Jetli Chung, Jason Teo |
---|---|
Format: | Article |
Language: | English English |
Published: |
Springer Nature
2023
|
Subjects: | |
Online Access: | https://eprints.ums.edu.my/id/eprint/38461/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/38461/2/FULL%20TEXT.pdf |
Similar Items
-
Stigma dan penerimaan masyarakat
terhadap pesakit mental dan cara
berhadapan dengan isu penyakit
mental
by: Abdullah @ Mohd. Nor, Hilwa, et al.
Published: (2022) -
Development of a scale to measure shared problem-solving and decision-making in mental healthcare
by: Shoesmith, Wendy Diana, et al.
Published: (2022) -
COVID-19 pandemic - A review and assessing higher education institution undergraduate student’s mental health
by: Mohd Amiruddin Mohd Kassim, et al.
Published: (2020) -
Unique challenges for mental health in inpatient settings amid the COVID-19 pandemic: Perspective from Sabah
by: Sze, Chet Lee, et al.
Published: (2020) -
Obesity and mental health issues among healthcare workers: a cross-sectional study in Sabah, Malaysia
by: Narinderjeet Kaur Dadar Singh, et al.
Published: (2020)