Natural Language Processing for Risk Assessment: Identifying SI/SS in Psychiatric Notes

2 Data

2.1 Data Sources

2.2 SS and SI Categories

3 Methods

3.1 Lexicon Creation and Expansion

3.2 Annotations

3.3 System Description

4 Results

4.1 Demographics and 4.2 System Performance

5 Discussion

5.1 Limitations

6 Conclusion, Reproducibility, Funding, Acknowledgments, Author Contributions, and References

SUPPLEMENTARY

Guidelines for Annotating Social Support and Social Isolation in Clinical Notes

Other Supervised Models

5 DISCUSSION

This study presents rule- and LLM-based NLP systems to identify fine-grained categories of SS and SI in clinical notes of psychiatric patients. A primary goal of the study was to develop and validate two portable and open-source NLP systems. Given that none of the selected clinical notes were associated with ICD codes indicating SI, the development of both NLP systems enabled the identification and subcategorization of this risk ...