Summary of Predicting Suicidal Behavior Among Indian Adults Using Childhood Trauma, Mental Health Questionnaires and Machine Learning Cascade Ensembles, by Akash K Rao et al.
Predicting suicidal behavior among Indian adults using childhood trauma, mental health questionnaires and machine learning cascade ensembles
by Akash K Rao, Gunjan Y Trivedi, Riri G Trivedi, Anshika Bajpai, Gajraj Singh Chauhan, Vishnu K Menon, Kathirvel Soundappan, Hemalatha Ramani, Neha Pandya, Varun Dutt
First submitted to arxiv on: 31 Jan 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Machine learning algorithms have emerged as a promising tool for predicting suicidal behavior, but their efficacy in the Indian context has not been explored. This study aimed to develop and evaluate different machine learning models and ensembles to predict suicide behavior based on childhood trauma, mental health parameters, and behavioral factors. The researchers used data from 391 individuals from a wellness center in India, acquiring information through standardized questionnaires. Their results showed that cascade ensemble learning methods using support vector machines, decision trees, and random forests achieved an accuracy of 95.04% in classifying suicidal behavior using childhood trauma and mental health questionnaire data. These findings highlight the potential of machine learning ensembles to identify individuals with suicidal tendencies, enabling targeted interventions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Machine learning is a way for computers to learn from data without being programmed. Researchers used this technology to see if they could predict when someone might hurt themselves. They took information from 391 people in India and looked at things like what happened to them as kids and how they’re feeling now. The computer program did really well, predicting suicide attempts with 95% accuracy! This means that in the future, we might be able to use computers to help identify people who need extra support before it’s too late. |
Keywords
* Artificial intelligence * Machine learning
