Author: Maheshwari, Shubham; Pahwa, Khushbu; Sethi, Tavpritesh
Title: WiseR: An end-to-end structure learning and deployment framework for causal graphical models Cord-id: 8co83ayl Document date: 2021_8_16
ID: 8co83ayl
Snippet: Structure learning offers an expressive, versatile and explainable approach to causal and mechanistic modeling of complex biological data. We present wiseR, an open source application for learning, evaluating and deploying robust causal graphical models using graph neural networks and Bayesian networks. We demonstrate the utility of this application through application on for biomarker discovery in a COVID-19 clinical dataset.
Document: Structure learning offers an expressive, versatile and explainable approach to causal and mechanistic modeling of complex biological data. We present wiseR, an open source application for learning, evaluating and deploying robust causal graphical models using graph neural networks and Bayesian networks. We demonstrate the utility of this application through application on for biomarker discovery in a COVID-19 clinical dataset.
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