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Fig. 10 | BMC Medical Informatics and Decision Making

Fig. 10

From: Developing a novel causal inference algorithm for personalized biomedical causal graph learning using meta machine learning

Fig. 10

Visualization of Learned Graphs. We visualize the graphs learned from different algorithms. As shown in the figure, with an increasing number of tasks (from 5 to 10), our algorithm can utilize additional data to increase its performance, resulting in fewer false positive edges. In the depicted adjacency matrices, a dark hue signifies a value of 0, while a bright yellow indicates a value of 1. The various shades of green represent the probability estimates produced by each algorithm

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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