Table S15 from The Spatial Structure of the Tumor Immune Microenvironment Can Explain and Predict Patient Response in High-Grade Serous Carcinoma

Table S15 from The Spatial Structure of the Tumor Immune Microenvironment Can Explain and Predict Patient Response in High-Grade Serous Carcinoma

<p>Table S15. Ranking of feature importance in the random forest model main text results. Ranking of median Gini importance values for all features across 500 evaluations predicting OS and PFS.</p>

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Bibliographic Details
Main Author: Lucy B. Van Kleunen (20104025) (author)
Other Authors: Mansooreh Ahmadian (20104028) (author), Miriam D. Post (15090798) (author), Rebecca J. Wolsky (20104031) (author), Christian Rickert (20104034) (author), Kimberly R. Jordan (15049505) (author), Junxiao Hu (16157686) (author), Jennifer K. Richer (14946445) (author), Lindsay W. Brubaker (19330142) (author), Nicole Marjon (18175977) (author), Kian Behbakht (15098439) (author), Matthew J. Sikora (14932044) (author), Benjamin G. Bitler (15027282) (author), Aaron Clauset (10453891) (author)
Published: 2024
Subjects:
Cancer
Cancer Detection and Diagnosis
Methods and Technology
Biomarkers
Imaging biomarkers
Prognostic biomarkers
Biostatistics
Computational Methods
Artificial intelligence & machine learning
Mathematical modeling
Gynecological Cancers
Ovarian cancer
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