Detection of suicidality from medical text using privacy-preserving large language models: feature
BackgroundAttempts to use artificial intelligence (AI) in psychiatric disorders show moderate success, highlighting the potential of incorporating information from clinical assessments to improve the models. This study focuses on using large language models (LLMs) to detect suicide risk from medical...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
05 November 2024
|
| In: |
The British journal of psychiatry
Year: 2024, Jahrgang: 225, Heft: 6, Pages: 532-537 |
| ISSN: | 1472-1465 |
| DOI: | 10.1192/bjp.2024.134 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1192/bjp.2024.134 Verlag, kostenfrei, Volltext: http://www.cambridge.org/core/journals/the-british-journal-of-psychiatry/article/detection-of-suicidality-from-medical-text-using-privacypreserving-large-language-models/75E6B08AECDF68443C2594F421805FD9# 
|
| Verfasserangaben: | Isabella Catharina Wiest, Falk Gerrik Verhees, Dyke Ferber, Jiefu Zhu, Michael Bauer, Ute Lewitzka, Andrea Pfennig, Pavol Mikolas and Jakob Nikolas Kather |
MARC
| LEADER | 00000caa a2200000 c 4500 | ||
|---|---|---|---|
| 001 | 1923811673 | ||
| 003 | DE-627 | ||
| 005 | 20250717012041.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 250429s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1192/bjp.2024.134 |2 doi | |
| 035 | |a (DE-627)1923811673 | ||
| 035 | |a (DE-599)KXP1923811673 | ||
| 035 | |a (OCoLC)1528045038 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 084 | |a 11 |2 sdnb | ||
| 100 | 1 | |a Wiest, Isabella |d 1992- |e VerfasserIn |0 (DE-588)1198882956 |0 (DE-627)168103638X |4 aut | |
| 245 | 1 | 0 | |a Detection of suicidality from medical text using privacy-preserving large language models |b feature |c Isabella Catharina Wiest, Falk Gerrik Verhees, Dyke Ferber, Jiefu Zhu, Michael Bauer, Ute Lewitzka, Andrea Pfennig, Pavol Mikolas and Jakob Nikolas Kather |
| 264 | 1 | |c 05 November 2024 | |
| 300 | |b Illustrationen, Diagramme | ||
| 300 | |a 6 | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Gesehen am 29.04.2025 | ||
| 520 | |a BackgroundAttempts to use artificial intelligence (AI) in psychiatric disorders show moderate success, highlighting the potential of incorporating information from clinical assessments to improve the models. This study focuses on using large language models (LLMs) to detect suicide risk from medical text in psychiatric care.AimsTo extract information about suicidality status from the admission notes in electronic health records (EHRs) using privacy-sensitive, locally hosted LLMs, specifically evaluating the efficacy of Llama-2 models.MethodWe compared the performance of several variants of the open source LLM Llama-2 in extracting suicidality status from 100 psychiatric reports against a ground truth defined by human experts, assessing accuracy, sensitivity, specificity and F1 score across different prompting strategies.ResultsA German fine-tuned Llama-2 model showed the highest accuracy (87.5%), sensitivity (83.0%) and specificity (91.8%) in identifying suicidality, with significant improvements in sensitivity and specificity across various prompt designs.ConclusionsThe study demonstrates the capability of LLMs, particularly Llama-2, in accurately extracting information on suicidality from psychiatric records while preserving data privacy. This suggests their application in surveillance systems for psychiatric emergencies and improving the clinical management of suicidality by improving systematic quality control and research. | ||
| 650 | 4 | |a electronic health records | |
| 650 | 4 | |a Large language models | |
| 650 | 4 | |a natural language processing | |
| 650 | 4 | |a psychiatric disorder detection | |
| 650 | 4 | |a suicidality | |
| 700 | 1 | |a Verhees, Falk Gerrik |d 1993- |e VerfasserIn |0 (DE-588)1368412149 |0 (DE-627)1927974054 |4 aut | |
| 700 | 1 | |a Ferber, Dyke |e VerfasserIn |0 (DE-588)1171467079 |0 (DE-627)1040545629 |0 (DE-576)513746056 |4 aut | |
| 700 | 1 | |a Zhu, Jiefu |e VerfasserIn |4 aut | |
| 700 | 1 | |a Bauer, Michael |e VerfasserIn |4 aut | |
| 700 | 1 | |a Lewitzka, Ute |e VerfasserIn |0 (DE-588)1279114762 |0 (DE-627)183232138X |4 aut | |
| 700 | 1 | |a Pfennig, Andrea |d 1971- |e VerfasserIn |0 (DE-588)123870941 |0 (DE-627)706457633 |0 (DE-576)293919364 |4 aut | |
| 700 | 1 | |a Mikolas, Pavol |e VerfasserIn |4 aut | |
| 700 | 1 | |a Kather, Jakob Nikolas |d 1989- |e VerfasserIn |0 (DE-588)1064064914 |0 (DE-627)812897587 |0 (DE-576)423589091 |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t The British journal of psychiatry |d Cambridge : Cambridge University Press, 1963 |g 225(2024), 6, Seite 532-537 |h Online-Ressource |w (DE-627)320240754 |w (DE-600)2021500-9 |w (DE-576)09388849X |x 1472-1465 |7 nnas |a Detection of suicidality from medical text using privacy-preserving large language models feature |
| 773 | 1 | 8 | |g volume:225 |g year:2024 |g number:6 |g pages:532-537 |g extent:6 |a Detection of suicidality from medical text using privacy-preserving large language models feature |
| 856 | 4 | 0 | |u https://doi.org/10.1192/bjp.2024.134 |x Verlag |x Resolving-System |z kostenfrei |3 Volltext |
| 856 | 4 | 0 | |u http://www.cambridge.org/core/journals/the-british-journal-of-psychiatry/article/detection-of-suicidality-from-medical-text-using-privacypreserving-large-language-models/75E6B08AECDF68443C2594F421805FD9# |x Verlag |z kostenfrei |3 Volltext |
| 951 | |a AR | ||
| 992 | |a 20250429 | ||
| 993 | |a Article | ||
| 994 | |a 2024 | ||
| 998 | |g 1064064914 |a Kather, Jakob Nikolas |m 1064064914:Kather, Jakob Nikolas |d 910000 |d 910100 |e 910000PK1064064914 |e 910100PK1064064914 |k 0/910000/ |k 1/910000/910100/ |p 9 |y j | ||
| 998 | |g 1171467079 |a Ferber, Dyke |m 1171467079:Ferber, Dyke |d 910000 |d 910100 |e 910000PF1171467079 |e 910100PF1171467079 |k 0/910000/ |k 1/910000/910100/ |p 3 | ||
| 998 | |g 1198882956 |a Wiest, Isabella |m 1198882956:Wiest, Isabella |d 60000 |d 61100 |e 60000PW1198882956 |e 61100PW1198882956 |k 0/60000/ |k 1/60000/61100/ |p 1 |x j | ||
| 999 | |a KXP-PPN1923811673 |e 4715037033 | ||
| BIB | |a Y | ||
| SER | |a journal | ||
| JSO | |a {"origin":[{"dateIssuedKey":"2024","dateIssuedDisp":"05 November 2024"}],"person":[{"display":"Wiest, Isabella","family":"Wiest","given":"Isabella","role":"aut"},{"display":"Verhees, Falk Gerrik","role":"aut","given":"Falk Gerrik","family":"Verhees"},{"display":"Ferber, Dyke","given":"Dyke","role":"aut","family":"Ferber"},{"role":"aut","given":"Jiefu","family":"Zhu","display":"Zhu, Jiefu"},{"display":"Bauer, Michael","family":"Bauer","given":"Michael","role":"aut"},{"display":"Lewitzka, Ute","family":"Lewitzka","given":"Ute","role":"aut"},{"family":"Pfennig","given":"Andrea","role":"aut","display":"Pfennig, Andrea"},{"display":"Mikolas, Pavol","given":"Pavol","role":"aut","family":"Mikolas"},{"display":"Kather, Jakob Nikolas","family":"Kather","role":"aut","given":"Jakob Nikolas"}],"relHost":[{"part":{"year":"2024","volume":"225","pages":"532-537","issue":"6","text":"225(2024), 6, Seite 532-537","extent":"6"},"id":{"eki":["320240754"],"issn":["1472-1465"],"zdb":["2021500-9"]},"titleAlt":[{"title":"BJPsych"},{"title":"BJP"}],"pubHistory":["109.1963 -"],"name":{"displayForm":["publ. by the Royal College of Psychiatrists"]},"corporate":[{"display":"Royal College of Psychiatrists","role":"isb"}],"disp":"Detection of suicidality from medical text using privacy-preserving large language models featureThe British journal of psychiatry","recId":"320240754","physDesc":[{"extent":"Online-Ressource"}],"title":[{"title_sort":"British journal of psychiatry","title":"The British journal of psychiatry","subtitle":"BJPsych"}],"note":["Gesehen am 06.06.2018"],"language":["eng"],"type":{"bibl":"periodical","media":"Online-Ressource"},"origin":[{"publisher":"Cambridge University Press ; The Royal College of Psychiatrists","publisherPlace":"Cambridge ; London","dateIssuedKey":"1963","dateIssuedDisp":"1963-"}]}],"title":[{"subtitle":"feature","title":"Detection of suicidality from medical text using privacy-preserving large language models","title_sort":"Detection of suicidality from medical text using privacy-preserving large language models"}],"language":["eng"],"type":{"media":"Online-Ressource","bibl":"article-journal"},"note":["Gesehen am 29.04.2025"],"recId":"1923811673","physDesc":[{"noteIll":"Illustrationen, Diagramme","extent":"6 S."}],"name":{"displayForm":["Isabella Catharina Wiest, Falk Gerrik Verhees, Dyke Ferber, Jiefu Zhu, Michael Bauer, Ute Lewitzka, Andrea Pfennig, Pavol Mikolas and Jakob Nikolas Kather"]},"id":{"doi":["10.1192/bjp.2024.134"],"eki":["1923811673"]}} | ||
| SRT | |a WIESTISABEDETECTIONO0520 | ||