In addition to lexicons, other types of external knowledge that could be integrated into transformer-based models for enhanced depression symptom estimation include:
Clinical Guidelines: Incorporating clinical guidelines related to depression symptoms and diagnostic criteria can provide valuable context for the model to make more informed predictions.
Medical Literature: Utilizing information from medical literature and research studies on depression can help the model understand the latest findings and trends in symptom manifestation.
Therapist Notes: Integrating anonymized therapist notes or session summaries can offer insights into the patient's history, progress, and specific symptoms discussed during therapy sessions.
Biological Markers: Incorporating data on biological markers associated with depression, such as genetic predispositions or neuroimaging findings, can provide a more comprehensive view of the individual's condition.
Linguistic Patterns: Analyzing linguistic patterns specific to depression, such as rumination, cognitive distortions, or avoidance behaviors, can further refine the model's understanding of language indicative of mental health issues.