Authors reply: "Evaluating the efficacy of large language models in predicting intensive care unit admission needs".
| Title: | Authors reply: "Evaluating the efficacy of large language models in predicting intensive care unit admission needs". |
|---|---|
| Authors: | Turan Eİ; Department of Anesthesiology, Istanbul Health Science University Kanuni Sultan Süleyman Education and Training Hospital, Istanbul, Turkey. Electronic address: enginihsan@hotmail.com.; Baydemir AE; Department of Anesthesiology, Basaksehir Cam ve Sakura City Hospital, Istanbul, Turkey.; Turan ZP; Department of Anesthesiology, Istanbul Health Science University Sisli Etfal Education and Training Hospital, Istanbul, Turkey.; Şahin AS; Department of Anesthesiology, Istanbul Health Science University Kanuni Sultan Süleyman Education and Training Hospital, Istanbul, Turkey. |
| Source: | Journal of critical care [J Crit Care] 2026 Apr 09; Vol. 94, pp. 155585. Date of Electronic Publication: 2026 Apr 09. |
| Publication Model: | Ahead of Print |
| Publication Type: | Letter |
| Language: | English |
| Journal Info: | Publisher: W.B. Saunders Country of Publication: United States NLM ID: 8610642 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1557-8615 (Electronic) Linking ISSN: 08839441 NLM ISO Abbreviation: J Crit Care Subsets: MEDLINE |
| Imprint Name(s): | Publication: Philadelphia Pa : W.B. Saunders; Original Publication: Orlando, FL : Grune & Stratton, c1986- |
| Competing Interests: | Declaration of competing interest The authors declare that they have not received any financial support for the conduct of this research or the preparation of this manuscript. Furthermore, there are no conflicts of interest to disclose by any of the authors. In this study, ChatGPT-5.3 has been utilized to enhance the readability of the paper. |
| Entry Date(s): | Date Created: 20260410 Latest Revision: 20260410 |
| Update Code: | 20260411 |
| DOI: | 10.1016/j.jcrc.2026.155585 |
| PMID: | 41962412 |
| Database: | MEDLINE |
Letter