Confound Removal and Normalization in Practice: A Neuroimaging Based Sex Prediction Case Study

• Published in: Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track Vol. 12461; pp. 3 - 18
• Main Authors: More, Shammi, Eickhoff, Simon B., Caspers, Julian, Patil, Kaustubh R.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 01.01.2021; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Confound removal; Generalization; Interpretability; Neuroimaging application; Sex classification

Machine learning (ML) methods are increasingly being used to predict pathologies and biological traits using neuroimaging data. Here controlling for confounds is essential to get unbiased estimates of generalization performance and to identify the features driving predictions. However, a systematic...