A time series algorithm to predict surgery in neonatal necrotizing enterocolitis
The LSTM model with FL exhibits high precision and recall in forecasting the need for surgical intervention 1 or 2 days ahead. This predictive capability holds promise for enhancing infants' outcomes by facilitating timely clinical decisions.
Authors
- Ling Qiu (ORCID: https://orcid.org/0000-0003-4011-2042)
- Xiao Liu (ORCID: https://orcid.org/0000-0002-0919-4820)
- Lu-Quan Li (ORCID: https://orcid.org/0000-0002-5496-6578)
- Xiaochen Liu (ORCID: https://orcid.org/0000-0002-3835-5558)
- Ling Li (ORCID: https://orcid.org/0000-0002-3374-4511)
- Lei Bao (ORCID: https://orcid.org/0000-0002-7834-4327)
- Feilong Chen (ORCID: https://orcid.org/0000-0002-4860-8483)
- Cheng Cui (ORCID: https://orcid.org/0000-0001-6446-0127)
- Huan Sun
Institutions
- Chongqing University of Posts and Telecommunications (CN)
- China University of Mining and Technology (CN)
- Health and Family Planning Commission of Sichuan Province (CN)
- Maternal and Child Health Hospital of Sichuan Province (CN)
- Children's Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1186/s12911-024-02695-w
- Citations
- 4
- Primary Topic
- Infant Nutrition and Health
- Type
- article
- Field-Weighted Citation Impact
- 1.24
Funders
- Natural Science Foundation of Chongqing