Transformer-based deep learning model for real-time prediction of intraoperative hypotension using dynamic time-series vital signs: A retrospective study.
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| Title: | Transformer-based deep learning model for real-time prediction of intraoperative hypotension using dynamic time-series vital signs: A retrospective study. |
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| Authors: | Zhu S; Department of Anesthesiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China., Shi W; Department of Anesthesiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China., Qian H; Nanjing Qicheng Medical Technology Co., Ltd., Nanjing, China., Tong X; Nanjing Qicheng Medical Technology Co., Ltd., Nanjing, China., Hu R; Nanjing Qicheng Medical Technology Co., Ltd., Nanjing, China., Bo J; Department of Anesthesiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China., Gu X; Department of Anesthesiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China. |
| Source: | PLoS medicine [PLoS Med] 2026 Mar 25; Vol. 23 (3), pp. e1005024. Date of Electronic Publication: 2026 Mar 25 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101231360 Publication Model: eCollection Cited Medium: Internet ISSN: 1549-1676 (Electronic) Linking ISSN: 15491277 NLM ISO Abbreviation: PLoS Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1549-1676 |
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| DOI: | 10.1371/journal.pmed.1005024 |
