Machine Learning-Based Suicide Risk Assessment and Intervention Strategies for Depression - Yousif, Muhammad; Nagra, Arfan Ali; Abubakar, Muhammad; Ali, Farman; Saleem, Shoaib; Khan, Hamza Wazir; Haider, Muhammad Hasham (UMT Artificial Intelligence Review, 2024)
Suicide is a global issue, primarily caused by depression. Over the past three decades, the World Health Organization reports that a considerable number of people have died by suicide. This study uses machine-learning models like Naive Bayes and logistic regression, to predict suicide risk using a dataset of social media posts. Previous research has used SVM and random forest, but deep learning techniques could improve accuracy by analyzing visual and auditory data. This would simplify mental health professionals' work and move away from traditional methods. In today’s digital world, leveraging digital tools can make significant progress in suicide prevention and mental health support. Moreover, future developments may include refined clinical reports with human experts, providing researchers with more effective tools for improving mental health outcomes