Unraveling Radiomics Complexity: Strategies for Optimal Simplicity in Predictive Modeling

no code implementations • 5 Jul 2024 • Mahdi Ait Lhaj Loutfi, Teodora Boblea Podasca, Alex Zwanenburg, Taman Upadhaya, Jorge Barrios, David R. Raleigh, William C. Chen, Dante P. I. Capaldi, Hong Zheng, Olivier Gevaert, Jing Wu, Alvin C. Silva, Paul J. Zhang, Harrison X. Bai, Jan Seuntjens, Steffen Löck, Patrick O. Richard, Olivier Morin, Caroline Reinhold, Martin Lepage, Martin Vallières

Purpose: Develop a methodology and tools to identify and explain the smallest set of predictive radiomic features.

Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls

no code implementations • 1 Feb 2022 • Farhad Maleki, Katie Ovens, Rajiv Gupta, Caroline Reinhold, Alan Spatz, Reza Forghani

We investigate three methodological pitfalls: (1) violation of independence assumption, (2) model evaluation with an inappropriate performance indicator or baseline for comparison, and (3) batch effect.

BIG-bench Machine Learning Data Augmentation +2