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DSPONVNet: a multimodal deep learning model integrating intraoperative monitoring and clinical features for predicting postoperative nausea and vomiting risk

Crossref DOI link: https://doi.org/10.1186/s12874-026-02845-w

Published Online: 2026-04-02

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Liu, Lixin

Wang, Haifeng

Wei, Yi

Kong, Di

Xue, Zhaoping

Liu, Ying
Funding

Funding for this research was provided by:

Beijing Medical Award Foundation (YXJL-2024-1376-0473)
License Information

Text and Data Mining valid from 2026-04-02

Accepted Manuscript valid from 2026-04-02
More Information

Article History

Received: 11 June 2025

Accepted: 24 March 2026

First Online: 2 April 2026

Declarations

:

: This study was approved by the Ethics Committee of the First Hospital of Jilin University (protocol code: 2024-MS-117, approval date: March 8, 2024), and conducted in accordance with the Declaration of Helsinki. Given the retrospective design and anonymization of patient data, the requirement for individual informed consent was waived.

: Not applicable.

: The authors declare no competing interests.

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