[2208.06648] Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness

PDF view of the paper entitled Inclusion Strategies under Clinical presence: The Impact on Al -Insaf Al -Khwarizmi, by Vincent Jenusily and 3 other authors

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a summary:The risk of machine learning enhances the biases in the data, and as we discuss in this work, in what is absent from the data. In health care, societal biases and decisions are patterns of missing data, however the effects of equity algorithms in the loss of their own group are poorly understood. The way we deal with health care can have harmful effects on the estuary of the estuary. Our work is wondering about the current recommendations and practices aimed at dealing with lost data with a focus on its impact on algorithm, and provides a way forward. Specifically, we consider the theoretical foundations of the current recommendations as well as their experimental predictive performance and the corresponding corresponding equity through sub -shows. Our results show that current practices for dealing with missing loss lack the initial foundations, are separated from the facts of missing mechanisms in health care, and can be counterproductive. For example, it appears that the preference of the group’s inclusion strategy can be misleading and exacerbating the prediction. Then we build the results we reached to propose a framework for experimental guidance options and the associated reporting framework. Our work constitutes an important contribution to the recent efforts made by organizers and practitioners in dealing with real data facts, and promoting responsible and transparent publication of automated learning systems. We explain the practical benefit of the proposed framework through the experience on the databases used widely, where we explain how the proposed framework can direct the selection of inclusion strategies, which allows us to choose from the strategies that result from equal prediction performance in general, but it represents the characteristics of different algorithm justice.