Published on in Vol 7 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/42452, first published
.
![Real-Time Prediction of Sepsis in Critical Trauma Patients: Machine Learning–Based Modeling Study Real-Time Prediction of Sepsis in Critical Trauma Patients: Machine Learning–Based Modeling Study](https://asset.jmir.pub/assets/4f715be37b3fc8c29663f41389be738a.png 480w,https://asset.jmir.pub/assets/4f715be37b3fc8c29663f41389be738a.png 960w,https://asset.jmir.pub/assets/4f715be37b3fc8c29663f41389be738a.png 1920w,https://asset.jmir.pub/assets/4f715be37b3fc8c29663f41389be738a.png 2500w)
Journals
- Mahyoub M, Yadav R, Dougherty K, Shukla A. Development and validation of a machine learning model integrated with the clinical workflow for early detection of sepsis. Frontiers in Medicine 2023;10 View
- Cao K, Zhang T, Huang J. Advanced hybrid LSTM-transformer architecture for real-time multi-task prediction in engineering systems. Scientific Reports 2024;14(1) View