Enhanced prediction of suicidal ideation using dimensional subdomains from DSM-5 Level 1 Cross-Sectional Symptom Scale with neural networks
Muhammed Ballı, Aslı Ercan Doğan, Şevin Hun Şenol, Hale Yapıcı Eser · FENS Forum 2024
Identification of suicidal ideation is crucial for clinical intervention and prevention.The study presented below attempts to enhance the predictive validity of neural network models based on suicidal ideation with the help of indirect psychometric indications, but without any direct questioning with regard to self-harm.We analyzed a dataset of 935 individuals aged between 18 and 40 years (mean age 23.5 years) obtained from the Koç University Psychotherapy Center. The initial model included demographic information, lifestyle factors, items of the DSM5 Level 1 Cross-Sectional Scale (except item
ePoster · Neuroscience