Identification of metabolomics-based biomarker discovery in individuals with down syndrome utilizing kernel-tree model-enhanced explainable artificial intelligence methodology.
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| Title: | Identification of metabolomics-based biomarker discovery in individuals with down syndrome utilizing kernel-tree model-enhanced explainable artificial intelligence methodology. |
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| Authors: | Colak C; Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya, Türkiye., Yagin FH; Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya, Türkiye., Yagin B; Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya, Türkiye., Alkhateeb A; Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada., Al-Rawi MBA; Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia., Akhloufi MA; Perception, Robotics and Intelligent Machines (PRIME) Lab, Department Computer Science, Université de Moncton, Moncton, NB, Canada., Aghaei M; Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU), Alesund, Norway.; Department of Sustainable Systems Engineering (INATECH), Albert Ludwigs University of Freiburg, Freiburg, Germany. |
| Source: | Frontiers in molecular biosciences [Front Mol Biosci] 2025 Apr 09; Vol. 12, pp. 1567199. Date of Electronic Publication: 2025 Apr 09 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101653173 Publication Model: eCollection Cited Medium: Print ISSN: 2296-889X (Print) Linking ISSN: 2296889X NLM ISO Abbreviation: Front Mol Biosci Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2296-889X |
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| DOI: | 10.3389/fmolb.2025.1567199 |
