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. 2018 Jun 27;8:9774. doi: 10.1038/s41598-018-27997-8

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Bayesian networks based on the complete data at different times. (A) Group 1 data at BL (197 participants). (B) Group 1 data, assessments conducted at least once during the M18-54 time interval (130 participants). (C) Group 2 longitudinal data at BL (133 participants) including time-evolved features. (D) Group 2 longitudinal data, assessments conducted at least once during the M18-54 time interval including time-evolved features. The thickness of arrows represents the strength of the probabilistic influences between variables. As the Group 2 set uses longitudinal data focuses, the ApoE feature was disregarded due to its unchanging nature.