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Supplementary Figure S1 from Performance of Statistical and Machine Learning Risk Prediction Models for Surveillance Benefits and Failures in Breast Cancer Survivors

Year: 2023

Type: supplementary-materials

Abstract: Supplementary Figure S1 shows frequency of predictor inclusion in regression-based models for surveillance failure and benefit across imputed datasets.

DOI: 10.1158/1055-9965.22494799

Authors: Yu-Ru Su, Diana S.M. Buist, Janie M. Lee, Laura Ichikawa, Diana L. Miglioretti, Erin J. Aiello Bowles, Karen J. Wernli, Karla Kerlikowske, Anna Tosteson, Kathryn P. Lowry, Louise M. Henderson, Brian L. Sprague, Rebecca A. Hubbard

Language: English

Topic: Global Cancer Incidence and Screening

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

OpenAlex ID: W4362480053

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