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csbj3253.section.3:4 Children: Item: Title: 3.1 Analysis of requirements Destination: csbj3253.subsection.1:6 Children: Item: Title: 3.1.1 Definition of prediction targets Destination: csbj3253.subsubsection.1:7 Item: Title: 3.1.2 System design Destination: csbj3253.subsubsection.2:10 Item: Title: 3.2 Development of ML models Destination: csbj3253.subsection.2:11 Children: Item: Title: 3.2.1 Feature selection Destination: csbj3253.subsubsection.1:12 Item: Title: 3.2.2 Predictive models Destination: csbj3253.subsubsection.2:13 Item: Title: 3.2.3 Model explanations Destination: csbj3253.subsubsection.3:14 Item: Title: 3.3 Fairness Destination: csbj3253.subsection.3:15 Item: Title: 4 Results Destination: csbj3253.section.4:16 Children: Item: Title: 4.1 Feature selection Destination: csbj3253.subsection.1:17 Item: Title: 4.2 Definition of baseline variables Destination: csbj3253.subsection.2:19 Item: Title: 4.3 Predictive models Destination: csbj3253.subsection.3:21 Item: Title: 4.4 Web-based predictive platform Destination: csbj3253.subsection.4:25 Item: Title: 4.5 Ethical concerns Destination: csbj3253.subsection.5:26 Children: Item: Title: 4.5.1 Transparency and explainability Destination: csbj3253.subsubsection.1:27 Item: Title: 4.5.2 Data privacy and security Destination: csbj3253.subsubsection.2:29 Item: Title: 4.5.3 Gender bias analysis Destination: csbj3253.subsubsection.3:30 Item: Title: 4.5.4 Regulatory compliance Destination: csbj3253.subsubsection.4:32 Item: Title: 4.5.5 Clinical applicability Destination: csbj3253.subsubsection.5:33 Item: Title: 4.6 MCT personalization Destination: csbj3253.subsection.6:34 Children: Item: Title: 4.6.1 Present functional design Destination: csbj3253.subsubsection.1:35 Item: Title: 4.6.2 Challenges and strategic improvements Destination: csbj3253.subsubsection.2:36 Item: Title: 5 Discussion and conclusions Destination: csbj3253.section.5:37 Item: Title: CRediT authorship contribution statement Destination: csbj3253.section.5:38 Item: Title: Funding Destination: csbj3253.section.5:39 Item: Title: Declaration of competing interest Destination: csbj3253.section.5:40 Item: Title: Acknowledgements Destination: csbj3253.section.5:41 Item: Title: Appendix A Supplementary material Destination: csbj3253.appendix.1:42 Item: Title: References Destination: csbj3253.section.5:44 Info: Title: An artificial intelligence-based platform for personalized predictions of Metacognitive Training effectiveness Author: Caroline König Subject: Computational and Structural Biotechnology Journal, 28 (2025) 281-293. doi:10.1016/j.csbj.2025.07.051 Keywords: Personalized medicine,Explainable artificial intelligence,Feature selection,Fairness,Metacognitive Training,Mental health Creator: Elsevier Producer: Acrobat Distiller 8.1.0 (Windows) CreationDate: Sat Aug 09 23:04:35 CEST 2025 ModDate: Mon Aug 11 10:48:22 CEST 2025 ID: 0xf854371f5d5a482dc8340434e70d439a, 0x3951249785f9b6d1d9ee5b8d9fd73665 Filters: 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Computational and Structural Biotechnology Journal, 28 (2025) 281-293. doi:10.1016/j.csbj.2025.07.051 Personalized medicine Explainable artificial intelligence Feature selection Fairness Metacognitive Training Mental health An artificial intelligence-based platform for personalized predictions of Metacognitive Training effectiveness Caroline König Pedro Copado Alfredo Vellido Àngela Nebot Cecilio Angulo Maria Lamarca Vanessa Acuña Fabrice Berna Steffen Moritz Łukasz Gawęda Susana Ochoa VoR 11th August 2025 Acrobat Distiller 8.1.0 (Windows) Personalized medicine,Explainable artificial intelligence,Feature selection,Fairness,Metacognitive Training,Mental health 11th August 2025 sciencedirect.com elsevier.com true 2010-04-23 7.0.1 10.1016/j.csbj.2025.07.051 noindex journal © 2025 The Author(s). 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