Development of depression detection algorithm using text scripts of routine psychiatric interview
Bibliographic Data
This is a qualitative and retrospective study to develop a tool to detect depression against patients without depression based on the text scripts of psychiatric interview, suggesting a novel and practical approach to understand the emotional characteristics of depression patients and to use them to detect the diagnosis of depression based on machine learning methods. This model could assist psychiatrists in clinical settings who conduct routine conversations with patients using text transcripts of the interviews
Algorithm · Anger · Anxiety · Conversation · Depression (economics · Disgust · Major depressive disorder · Major depressive episode · Mood · Psychiatric history · Psychiatric interview · Psychiatry · Sadness · Surprise · Clinical Psychology · Computer Science · Medicine · Mental Health Research Topics · Mental Health Treatment and Access · Psychology · Psychosomatic Disorders and Their Treatments · Social Psychology
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |