Interpretable Feature Extraction from Clinical Notes for Sepsis Prediction: Comparing Rule-Based, LLM, and Hybrid Approaches.
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| Title: | Interpretable Feature Extraction from Clinical Notes for Sepsis Prediction: Comparing Rule-Based, LLM, and Hybrid Approaches. |
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| Authors: | Frey N; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany., Meyer-Eschenbach F; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany.; Clinical Study Center, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Germany., Voge L; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany., Ruhm L; Clinical Study Center, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Germany., Wagnitz J; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany., Näher AF; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany., Grünewald E; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany., Nothacker J; Clinical Study Center, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Germany., von Kalle C; Clinical Study Center, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Germany., Kumpf O; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany., Balzer F; Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Germany. |
| Source: | Studies in health technology and informatics [Stud Health Technol Inform] 2026 May 21; Vol. 336, pp. 989-993. |
| Publication Type: | Journal Article; Comparative Study |
| Journal Info: | Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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