Bayesian network for pain-related features of endometriosis.

Amber C. Kiser (18004200), Karen C. Schliep (8058098), Edgar Javier Hernandez (11561020), C. Matthew Peterson (18004203), Mark Yandell (61663), Karen Eilbeck (598165)
2024 · doi:10.1371/journal.pone.0297998.g002 · W6885918494
other OA: green CC0
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Abstract

Nodes correspond to pain-related features, subfertility, and diagnosis while the lines represent conditional dependencies between the features. Pain types are outlined in blue, while pain locations are outlined in pink. The color of the node indicates the proximity to the diagnosis node, including 1st, 2nd, 3rd, and 4th degree connections. The net has been moralized.
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An artificial intelligence approach for investigating multifactorial pain-related features of endometriosis Fig 2 Bayesian network for pain-related features of endometriosis. Nodes correspond to pain-related features, subfertility, and diagnosis while the lines represent conditional dependencies between the features. Pain types are outlined in blue, while pain locations are outlined in pink. The color of the node indicates the proximity to the diagnosis node, including 1st, 2nd, 3rd, and 4th degree connections. The net has been moralized.

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endometriosis

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last seen: 2026-05-13T19:02:20.592813+00:00
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