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Updated: Feb 10, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Identifying cytokine predictors of cognitive functioning in breast cancer survivors up to 10 years post chemotherapy
Ashley M Henneghan1, Oxana Palesh2, Michelle Harrison3
1University of Texas MD Anderson Cancer Center, Neuro-Oncology, USA; University of Texas at Austin School of Nursing, USA.
Introduction:
The purpose of this study is to explore 13 cytokine predictors of chemotherapy-related cognitive impairment (CRCI) in breast cancer survivors (BCS) 6 months to 10 years after chemotherapy completion using a multivariate, non-parametric approach.
Methods:
Cross sectional data collection included completion of a survey, cognitive testing, and non-fasting blood from 66 participants. Data were analyzed using random forest regression to identify the most significant predictors for each of the cognitive test scores.
Results:
A different cytokine profile predicted each cognitive test. Adjusted R2 for each model ranged from 0.71-0.77 (p's < 9.50-10). The relationships between all the cytokine predictors and cognitive test scores were non-linear.
Conclusions:
Our findings are unique to the field of CRCI and suggest non-linear cytokine specificity to neural networks underlying cognitive functions assessed in this study.
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