Leveraging sMRI, Self-Attention Mechanisms, and Evolving Spiking Neural Networks for Enhanced Suicide Ideation Detection in Depressed Young Adults
Accurate assessment of suicide ideation (SI) risk in depressed young adults remains a critical challenge, with existing methods exhibiting limited effectiveness. This study proposes a novel machine learning approach leveraging Evolving Spiking Neural Networks (ESNN) to enhance SI risk detection util...
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| Main Authors: | , |
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| Format: | Thesis |
| Language: | English English English |
| Published: |
Institute of Advanced Engineering and Science (IAES)
2024
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/45396/3/DSVA_Corrine%20Francis.pdf http://ir.unimas.my/id/eprint/45396/4/Thesis%20Master_%20Corrine%20Francis%20-%2024%20pages.pdf http://ir.unimas.my/id/eprint/45396/5/Thesis%20Master_%20Corrine%20Francis.ftext.pdf http://ir.unimas.my/id/eprint/45396/ https://ijai.iaescore.com/index.php/IJAI/index |
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http://ir.unimas.my/id/eprint/45396/3/DSVA_Corrine%20Francis.pdfhttp://ir.unimas.my/id/eprint/45396/4/Thesis%20Master_%20Corrine%20Francis%20-%2024%20pages.pdf
http://ir.unimas.my/id/eprint/45396/5/Thesis%20Master_%20Corrine%20Francis.ftext.pdf
http://ir.unimas.my/id/eprint/45396/
https://ijai.iaescore.com/index.php/IJAI/index