Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities
South Korea has one of the highest suicide rates among countries in the Organisation for Economic Co-Operation and Development, and the suicide rate among people with disabilities is more than twice that of the general population. This study aimed to develop an artificial intelligence-based suicide...
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MDPI AG
2024-10-01
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| Series: | Life |
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| author | Jimin Han |
| author_facet | Jimin Han |
| author_sort | Jimin Han |
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| description | South Korea has one of the highest suicide rates among countries in the Organisation for Economic Co-Operation and Development, and the suicide rate among people with disabilities is more than twice that of the general population. This study aimed to develop an artificial intelligence-based suicide ideation prediction model for people with disabilities in order to provide a proactive approach for managing high-risk groups and offer evidence for establishing suicide prevention policies. The support vector machine, adaptive boost (AdaBoost), and bidirectional long short-term memory (Bi-LSTM) models were used in this study. Data from the Disability and Life Dynamics Panel for 2018–2021 were used. The performance of the models was evaluated based on the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). All the prediction models demonstrated excellent performance, with AUC > 0.80 (0.83–0.87). The best-performing models were AdaBoost (0.87) for accuracy, Bi-LSTM (0.90) for sensitivity, and AdaBoost (0.90) for specificity. This study is the first to develop an artificial intelligence-based suicide ideation prediction model for disabled people and is significant in that it suggests ways to pre-emptively manage groups at high risk for suicide, providing evidence for the establishment of suicide prevention policies. |
| format | Article |
| id | doaj-art-87b7f79568f94ff8a20ccd05f5858035 |
| institution | OA Journals |
| issn | 2075-1729 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
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| series | Life |
| spelling | doaj-art-87b7f79568f94ff8a20ccd05f58580352025-08-20T01:54:07ZengMDPI AGLife2075-17292024-10-011411137210.3390/life14111372Development of an AI-Based Suicide Ideation Prediction Model for People with DisabilitiesJimin Han0Department of Public Health, Korea University College of Medicine, Seoul 02841, Republic of KoreaSouth Korea has one of the highest suicide rates among countries in the Organisation for Economic Co-Operation and Development, and the suicide rate among people with disabilities is more than twice that of the general population. This study aimed to develop an artificial intelligence-based suicide ideation prediction model for people with disabilities in order to provide a proactive approach for managing high-risk groups and offer evidence for establishing suicide prevention policies. The support vector machine, adaptive boost (AdaBoost), and bidirectional long short-term memory (Bi-LSTM) models were used in this study. Data from the Disability and Life Dynamics Panel for 2018–2021 were used. The performance of the models was evaluated based on the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). All the prediction models demonstrated excellent performance, with AUC > 0.80 (0.83–0.87). The best-performing models were AdaBoost (0.87) for accuracy, Bi-LSTM (0.90) for sensitivity, and AdaBoost (0.90) for specificity. This study is the first to develop an artificial intelligence-based suicide ideation prediction model for disabled people and is significant in that it suggests ways to pre-emptively manage groups at high risk for suicide, providing evidence for the establishment of suicide prevention policies.https://www.mdpi.com/2075-1729/14/11/1372suicide ideationartificial intelligencepeople with disabilitiesprediction model |
| spellingShingle | Jimin Han Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities Life suicide ideation artificial intelligence people with disabilities prediction model |
| title | Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities |
| title_full | Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities |
| title_fullStr | Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities |
| title_full_unstemmed | Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities |
| title_short | Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities |
| title_sort | development of an ai based suicide ideation prediction model for people with disabilities |
| topic | suicide ideation artificial intelligence people with disabilities prediction model |
| url | https://www.mdpi.com/2075-1729/14/11/1372 |
| work_keys_str_mv | AT jiminhan developmentofanaibasedsuicideideationpredictionmodelforpeoplewithdisabilities |