TY - STD TI - Peters J, Janzing D, Schölkopf B. Elements of Causal Inference: Foundations and Learning Algorithms. Cambridge: MIT Press; 2017. ID - ref1 ER - TY - JOUR AU - Sperrin, M. AU - Martin, G. P. AU - Pate, A. AU - Staa, T. AU - Peek, N. AU - Buchan, I. PY - 2018 DA - 2018// TI - Using marginal structural models to adjust for treatment drop-in when developing clinical prediction models JO - Stat Med VL - 37 UR - https://doi.org/10.1002/sim.7913 DO - 10.1002/sim.7913 ID - Sperrin2018 ER - TY - JOUR AU - Greenland, S. AU - Pearl, J. AU - Robins, J. M. PY - 1999 DA - 1999// TI - Causal diagrams for epidemiologic research JO - Epidemiology. VL - 10 UR - https://doi.org/10.1097/00001648-199901000-00008 DO - 10.1097/00001648-199901000-00008 ID - Greenland1999 ER - TY - STD TI - Greenland S, Pearl J. Causal Diagrams: Wiley StatsRef. Statistics Reference Online; 2014. https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118445112.stat03732. UR - https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118445112.stat03732 ID - ref4 ER - TY - JOUR AU - Hernán, M. A. AU - Hernández-Díaz, S. AU - Werler, M. M. AU - Mitchell, A. A. PY - 2002 DA - 2002// TI - Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology JO - Am J Epidemiol VL - 155 UR - https://doi.org/10.1093/aje/155.2.176 DO - 10.1093/aje/155.2.176 ID - Hernán2002 ER - TY - JOUR AU - Janzing, D. AU - Schölkopf, B. PY - 2010 DA - 2010// TI - Causal inference using the algorithmic Markov condition JO - IEEE Trans Inf Theory VL - 56 UR - https://doi.org/10.1109/TIT.2010.2060095 DO - 10.1109/TIT.2010.2060095 ID - Janzing2010 ER - TY - BOOK AU - Schölkopf, B. AU - Janzing, D. AU - Peters, J. AU - Sgouritsa, E. AU - Zhang, K. AU - Mooij, J. PY - 2012 DA - 2012// TI - On Causal and Anticausal Learning. arXiv [cs. LG] ID - Schölkopf2012 ER - TY - BOOK AU - Brown, L. E. AU - Tsamardinos, I. PY - 2008 DA - 2008// TI - Markov blanket-based variable selection in feature space. Technical Report DSL TR-08-01 ID - Brown2008 ER - TY - STD TI - Fu S, Desmarais MC. Markov blanket based feature selection: a review of past decade. In: Proceedings of the world congress on engineering. Hong Kong: Newswood Ltd; 2010;1:321–8. ID - ref9 ER - TY - JOUR AU - Elshawi, R. AU - Al-Mallah, M. H. AU - Sakr, S. PY - 2019 DA - 2019// TI - On the interpretability of machine learning-based model for predicting hypertension JO - BMC Med Inform Decis Mak VL - 19 UR - https://doi.org/10.1186/s12911-019-0874-0 DO - 10.1186/s12911-019-0874-0 ID - Elshawi2019 ER - TY - CHAP AU - Koller, D. AU - Sahami, M. PY - 1996 DA - 1996// TI - Toward Optimal Feature Selection BT - ICML’96 Proceedings of the Thirteenth International Conference on International Conference on Machine Learning ID - Koller1996 ER - TY - STD TI - Pearl J. Probabilistic reasoning in intelligent systems: networks of plausible inference. San Francisco: Morgan Kaufmann; 1988. ID - ref12 ER - TY - CHAP AU - Yaramakala, S. AU - Margaritis, D. PY - 2005 DA - 2005// TI - Speculative Markov blanket discovery for optimal feature selection BT - Fifth IEEE International Conference on Data Mining (ICDM’05) ID - Yaramakala2005 ER - TY - STD TI - Pellet J-P, Elisseeff A. Using Markov Blankets for Causal Structure Learning. J Mach Learn Res. 2008;9:1295–342. ID - ref14 ER - TY - CHAP AU - Tsamardinos, I. AU - Aliferis, C. F. AU - Statnikov, A. R. AU - Statnikov, E. PY - 2003 DA - 2003// TI - Algorithms for large scale Markov blanket discovery BT - FLAIRS conference ID - Tsamardinos2003 ER - TY - JOUR AU - Kohavi, R. AU - John, G. H. PY - 1997 DA - 1997// TI - Wrappers for feature subset selection JO - Artif Intell VL - 97 UR - https://doi.org/10.1016/S0004-3702(97)00043-X DO - 10.1016/S0004-3702(97)00043-X ID - Kohavi1997 ER - TY - STD TI - Tsamardinos I, Aliferis CF. Towards principled feature selection: relevancy, filters and wrappers. AISTATS: Proceedings of the ninth International workshop on artificial intelligence and statistics; 2003. ID - ref17 ER - TY - BOOK AU - Yang, S. AU - Wang, H. AU - Hu, X. PY - 2019 DA - 2019// TI - Efficient Local Causal Discovery Based on Markov Blanket. arXiv [cs.AI] ID - Yang2019 ER - TY - STD TI - Austin PC, Steyerberg EW. The integrated calibration index (ICI) and related metrics for quantifying the calibration of logistic regression models. Stat Med. 2019;38:4051–65. ID - ref19 ER - TY - JOUR AU - Uddin, M. S. AU - Kabir, M. T. AU - Mamun, A. AU - Abdel-Daim, M. M. AU - Barreto, G. E. AU - Ashraf, G. M. PY - 2019 DA - 2019// TI - APOE and Alzheimer’s disease: evidence mounts that targeting APOE4 may combat Alzheimer’s pathogenesis JO - Mol Neurobiol VL - 56 UR - https://doi.org/10.1007/s12035-018-1237-z DO - 10.1007/s12035-018-1237-z ID - Uddin2019 ER - TY - STD TI - Lee JC, Kim SJ, Hong S, Kim Y. Diagnosis of Alzheimer’s disease utilizing amyloid and tau as fluid biomarkers. Exp Mol Med. 2019;51:1–10. ID - ref21 ER - TY - CHAP AU - Li, G. AU - Dai, H. AU - Tu, Y. PY - 2004 DA - 2004// TI - Identifying Markov Blankets Using Lasso Estimation BT - Advances in Knowledge Discovery and Data Mining PB - Springer CY - Berlin Heidelberg UR - https://doi.org/10.1007/978-3-540-24775-3_39 DO - 10.1007/978-3-540-24775-3_39 ID - Li2004 ER - TY - STD TI - Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating. Second edition. Cham: Springer; 2019. ID - ref23 ER - TY - STD TI - Piccininni M, Konigorski S, Rohmann JL, Kurth T. Directed Acyclic Graphs and causal thinking in clinical risk prediction modeling. arXiv [stat.ME]. 2020. http://arxiv.org/abs/2002.09414. Accessed 15 June 2020. UR - http://arxiv.org/abs/2002.09414 ID - ref24 ER -