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Opening the Black Box: Discovering and Explaining Hidden Variables in Type 2 Diabetic Patient Modelling.

, , , , , and . BIBM, page 1040-1044. IEEE Computer Society, (2018)

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Predicting Academic Performance: A Bootstrapping Approach for Learning Dynamic Bayesian Networks., , , , and . AIED (1), volume 11625 of Lecture Notes in Computer Science, page 26-36. Springer, (2019)The Prevalence of Errors in Machine Learning Experiments., , , , , , , , , and . IDEAL (1), volume 11871 of Lecture Notes in Computer Science, page 102-109. Springer, (2019)Opening the Black Box: Discovering and Explaining Hidden Variables in Type 2 Diabetic Patient Modelling., , , , , and . BIBM, page 1040-1044. IEEE Computer Society, (2018)Predicting Comorbidities Using Resampling and Dynamic Bayesian Networks with Latent Variables., , , , and . CBMS, page 205-206. IEEE Computer Society, (2017)A Photonic Topological Insulator Based on a Coupled Plasmonic Nanoparticle Array., and . IST, page 353-356. IEEE, (2018)Opening the black box: Personalizing type 2 diabetes patients based on their latent phenotype and temporal associated complication rules., , , , , and . Comput. Intell., 37 (4): 1460-1498 (2021)Opening the Black Box: Exploring Temporal Pattern of Type 2 Diabetes Complications in Patient Clustering Using Association Rules and Hidden Variable Discovery., , , , , and . CBMS, page 198-203. IEEE, (2019)A fair spectrum sharing approach in Cognitive Radio Networks.. CCSEIT, page 753-759. ACM, (2012)Predicting Disease Complications Using a Stepwise Hidden Variable Approach for Learning Dynamic Bayesian Networks., , , , , and . CBMS, page 106-111. IEEE Computer Society, (2018)