Salim Salmi
Datos Biográficos
| ID | 7785452 |
|---|---|
| NOMBRE | Salim Salmi |
| NOMBRES | Salim |
| APELLIDO | Salmi |
| FIRMA | SALMI S |
| AFILIACIONES | Centrum Wiskunde & Informatica |
| ORCID | 0000-0002-8342-4815 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2022 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 0 |
Deductively coding psychosocial autopsy interview data using a few-shot learning large language model
Background: Psychosocial autopsy is a retrospective study of suicide, aimed to identify emerging themes and psychosocial risk factors. It typically relies heavily on qualitative data from interviews or medical documentation. However, qualitative research has often been scrutinized for being prone to bias and is notoriously time- and cost-intensive. Therefore, the current study aimed to investigate if a Large Language Model (LLM) can be feasibly i…
Detecting changes in help seeker conversations on a suicide prevention helpline during the Covid− 19 pandemic
While mentions of distraction, social interaction and plans for suicide decreased, expressions of gratefulness for the helpline increased, highlighting the importance of contact to help seekers during the lockdown. Help seekers under 30, male or who live alone, showed changes that negatively related to suicidality and should be monitored closely
Sin obras prominentes en esta página.
Detecting changes in help seeker conversations on a suicide prevention helpline during the Covid− 19 pandemic
While mentions of distraction, social interaction and plans for suicide decreased, expressions of gratefulness for the helpline increased, highlighting the importance of contact to help seekers during the lockdown. Help seekers under 30, male or who live alone, showed changes that negatively related to suicidality and should be monitored closely
Deductively coding psychosocial autopsy interview data using a few-shot learning large language model
Background: Psychosocial autopsy is a retrospective study of suicide, aimed to identify emerging themes and psychosocial risk factors. It typically relies heavily on qualitative data from interviews or medical documentation. However, qualitative research has often been scrutinized for being prone to bias and is notoriously time- and cost-intensive. Therefore, the current study aimed to investigate if a Large Language Model (LLM) can be feasibly i…
Medicine (2 obras) · Mental Health via Writing (2 obras) · Pathology (2 obras) · Suicide and Self-Harm Studies (2 obras) · 2019-20 coronavirus outbreak (1 obras) · Artificial Intelligence (1 obras) · Biostatistics (1 obras) · Cause of death (1 obras) · Computer Science (1 obras) · Coronavirus disease 2019 (COVID-19 (1 obras)