AI-driven prognostics in pediatric bone marrow transplantation: a CAD approach with Bayesian and PSO optimization.

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Title: AI-driven prognostics in pediatric bone marrow transplantation: a CAD approach with Bayesian and PSO optimization.
Authors: Badawy M; Department of Computer Science and Information, Applied College, Taibah University, Medinah, 42353, Saudi Arabia. engbadawy@mans.edu.eg.; Computers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt. engbadawy@mans.edu.eg., AbdulAzeem Y; School of Computational Sciences and Artificial Intelligence, Zewail City of Science, Technology and Innovation, Giza, 12578, Egypt., ZainEldin H; Computers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt., Balaha HM; Computers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt.; Bioengineering Department, University of Louisville, Louisville, Kentucky, 40292, USA., Bamaqa A; Department of Computer Science and Information, Applied College, Taibah University, Medinah, 42353, Saudi Arabia., El-Agamy RF; Department of Information Systems, College of Computer Science and Engineering, Taibah University, Yanbu, 46421, Saudi Arabia.; Department of Computer Science, Faculty of Science, Tanta University, Tanta, 31527, Egypt., Sayed HA; Department of Information Systems, College of Computer Science and Engineering, Taibah University, Yanbu, 46421, Saudi Arabia.; Department of Computer Science, Faculty of Computers and Information, Assiut University, Assiut, 71516, Egypt., Elhosseini MA; Computers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt.; Department of Information Systems, College of Computer Science and Engineering, Taibah University, Yanbu, 46421, Saudi Arabia.
Source: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Oct 06; Vol. 25 (1), pp. 363. Date of Electronic Publication: 2025 Oct 06.
Publication Type: Journal Article
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
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ISSN:1472-6947
DOI:10.1186/s12911-025-03133-1