Using Artificial Intelligence for Early Detection of Suicidal Ideation

Author: Jeyalakshmi Poornalingam

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Abstract

Suicide continues to be a major global public health concern, taking the lives of more than 700,000 people each year. For prompt intervention and prevention, suicidal ideation must be identified early. This article examines how machine learning, natural language processing (NLP) and predictive analytics are used in artificial intelligence (AI) to detect early indicators of suicide thoughts. AI models have shown the ability to detect high-risk regarding suicidal ideation. This article examines how machine learning, natural language processing (NLP) and predictive analytics are used in artificial intelligence (AI) to detect early indicators of suicidal thoughts. By analysing social media posts, electronic health records, and wearable device data, AI models have demonstrated the potential to identify high-risk individuals with remarkable accuracy. This paper discusses the methodologies, datasets, challenges, and ethical considerations surrounding AI-based approaches to suicide prevention.

Keywords

Suicidal Ideation, Artificial Intelligence, Natural Language Processing, Machine Learning, Data Privacy and ethics, CLPsych 2019 Dataset

Conclusion

"Suicide is a serious public health issue that is preventable with timely, evidence-based interventions." (World Health Organization, 2021). AI holds immense promise for revolutionizing suicide prevention by enabling early detection of suicidal ideation. However, ethical concerns, data biases and the need for interpretability must be addressed to maximize its potential. Collaborative efforts across technology, healthcare, and policy domains are essential for leveraging AI responsibly in this critical area. Furthermore, building trust between users and clinicians will need making sure that AI models' decision-making processes are transparent. Continuous research and cooperation should also concentrate on enhancing AI tools' accuracy while reducing biases that can produce unfair results. Ultimately, utilizing AI to effectively prevent suicides and provide significant support to people in crisis, should be the ultimate purpose of the society, clinicians and researchers in the field.

References

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How to cite this article

Jeyalakshmi Poornalingam (2025). Using Artificial Intelligence for Early Detection of Suicidal Ideation. Biological Forum, 17(2): 39-41.