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Sepsis mortality prediction using machine learning and deep learning - a systematic review.

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Bibliographic Details
Title: Sepsis mortality prediction using machine learning and deep learning - a systematic review.
Authors: AbuHaweeleh MN; Department of Basic Medical Sciences, College of Medicine, Qatar University, Doha, 2713, Qatar.; Department of Urology, Ambulatory Care Center, Hamad Medical Corporation, Doha, Qatar., Chowdhury AT; Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, 1000, Bangladesh., Newaz M; Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, 1000, Bangladesh., Saha P; Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, 1000, Bangladesh., Islam KR; Faculty of Medicine, Department of Physiology, University Kebangsaan Malaysia, Kuala Lumpur, 56000, Malaysia., Kumar J; Faculty of Medicine, Department of Physiology, University Kebangsaan Malaysia, Kuala Lumpur, 56000, Malaysia., Chowdhury MEH; Department of Electrical Engineering, Qatar University, Doha, 2713, Qatar. mchowdhury@qu.edu.qa., Pedersen S; Department of Basic Medical Sciences, College of Medicine, Qatar University, Doha, 2713, Qatar. spedersen@qu.edu.qa.
Source: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Dec 10; Vol. 26 (1), pp. 16. Date of Electronic Publication: 2025 Dec 10.
Publication Type: Journal Article; Systematic Review
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1472-6947
DOI:10.1186/s12911-025-03286-z