GenomeForest: An Ensemble Machine Learning Classifier for Endometriosis.

Sadia Akter, Dong Xu, Susan C Nagel, John J Bromfield, Katherine E Pelch, Gilbert B Wilshire, Trupti Joshi
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020 · vol. 2020 , pp. 33–42 · PMID:32477621 · W3030731582
article OA: green CC0 ⤵ 18 in-corpus citations
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⚙ AI-generated summary by claude@2026-06, 2026-06-07 ⓘ

GenomeForest, an ensemble machine learning classifier, achieved a high score of 0.918 on a methylomics dataset for endometriosis detection.

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Abstract

score (0.918) for the methylomics dataset. We hope in the future a less invasive biopsy can be used to diagnose endometriosis using the findings from such ensemble machine learning classifiers, as demonstrated in this study.

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endometriosis

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Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

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