Prediction of mortality in sepsis patients using stacked ensemble machine learning algorithm
The random forest showed high accuracy in train and moderate accuracy in the test data. We suggest more regional open-access intensive care databases that can aid making machine learning a bigger support for healthcare personnel.
Authors
- Marimuthu Sappani (ORCID: https://orcid.org/0000-0002-8473-4241)
- TD Sudarsanam
- Melvin Joy (ORCID: https://orcid.org/0000-0001-9323-994X)
- Lakshmanan Jeyaseelan (ORCID: https://orcid.org/0000-0002-9090-3005)
- Mohan Babu (ORCID: https://orcid.org/0000-0003-4118-6406)
- VK Chandiraseharan
Institutions
- Christian Medical College, Vellore (IN)
- Mohammed Bin Rashid University of Medicine and Health Sciences (AE)
Publication Details
- Journal
- Journal of Postgraduate Medicine
- Published
- 2024-10-01
- DOI
- https://doi.org/10.4103/jpgm.jpgm_357_24
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00