Machine Learning Models Are Not Necessarily Biased When Constructed Properly: Evidence from Neuroimaging Studies. (arXiv:2205.13421v1 [cs.LG])

Despite the great promise that machine learning has offered in many fields of
medicine, it has also raised concerns about potential biases and poor
generalization across genders, age distributions, races and ethnicities,
hospitals, and data acquisition equipment and protocols. In the current study,
and in the context of three brain diseases, we provide experimental data which
support that when properly trained, machine learning models can generalize well
across diverse conditions and do not suffer from biases. Specifically, by using
multi-study …

arxiv evidence learning machine machine learning machine learning models neuroimaging studies