Thoth: An intelligent model for assisting individuals with suicidal ideation

  • Wesllei Felipe Heckler Unisinos
  • Juliano Varella de Carvalho Feevale
  • Jorge Luis Victória Barbosa Unisinos


Suicide causes approximately 800,000 deaths worldwide every year, which means one death by suicide every 40 seconds. Suicidal ideation is the first stage in the suicide risk scale, in which the individuals have thoughts regarding being dead. Thereby, suicide prevention strategies may focus on identifying and treating individuals with this severity level. Therefore, this article presents the summary of an Academic Master’s Dissertation that proposes Thoth, a computational model for assisting people suffering from suicidal ideation. The main scientific contribution of the Thoth is the personalized assistance for individuals at risk of suicidal ideation through the analysis of Context Information for anticipating the identification of future risks. The model gathers sensor, sociodemographic, and psychological data for future risk checking through Machine Learning models. Experiments showed that the models obtained F1-Score up to 94.12%. Based on the experiments, Thoth could act in a personalized manner, sending recommendations and alerts to patients and caregivers, respectively. Thus, this research provides an improvement in the assistance of individuals with suicidal ideation through the proposed model.

Palavras-chave: Context Information, Machine Learning, Mental Health, Patient Assistance, Suicidal Ideation, Suicide Prevention


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HECKLER, Wesllei Felipe; DE CARVALHO, Juliano Varella; BARBOSA, Jorge Luis Victória. Thoth: An intelligent model for assisting individuals with suicidal ideation. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 29. , 2023, Ribeirão Preto/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 23-26. ISSN 2596-1683. DOI: