TY  - JOUR
PY  - 2022//
TI  - Boamente: A Natural Language Processing-Based Digital Phenotyping Tool for Smart Monitoring of Suicidal Ideation
JO  - Healthcare (Basel, Switzerland)
A1  - Diniz, E.J.S.
A1  - Fontenele, J.E.
A1  - de Oliveira, A.C.
A1  - Bastos, V.H.
A1  - Teixeira, S.
A1  - Rabêlo, R.L.
A1  - Calçada, D.B.
A1  - Dos Santos, R.M.
A1  - de Oliveira, A.K.
A1  - Teles, A.S.
SP  - 
EP  - 
VL  - 10
IS  - 4
N2  - People at risk of suicide tend to be isolated and cannot share their thoughts. For this reason, suicidal ideation monitoring becomes a hard task. Therefore, people at risk of suicide need to be monitored in a manner capable of identifying if and when they have a suicidal ideation, enabling professionals to perform timely interventions. This study aimed to develop the Boamente tool, a solution that collects textual data from users' smartphones and identifies the existence of suicidal ideation. The solution has a virtual keyboard mobile application that passively collects user texts and sends them to a web platform to be processed. The platform classifies texts using natural language processing and a deep learning model to recognize suicidal ideation, and the results are presented to mental health professionals in dashboards. Text classification for sentiment analysis was implemented with different machine/deep learning algorithms. A validation study was conducted to identify the model with the best performance results. The BERTimbau Large model performed better, reaching a recall of 0.953 (accuracy: 0.955; precision: 0.961; F-score: 0.954; AUC: 0.954). The proposed tool demonstrated an ability to identify suicidal ideation from user texts, which enabled it to be experimented with in studies with professionals and their patients. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.<p /> <p>Language: en</p>
LA  - en
SN  - 2227-9032
UR  - http://dx.doi.org/10.3390/healthcare10040698
ID  - ref1
ER  -