Deep Learning and Medical Image Analysis: Epistemology and Ethical Issues

Abstract

Machine and deep learning methods applied to medicine seem to be a promising way to improve the perfor-mance in solving many issues from the diagnosis of a disease to the prediction of personalized therapies byanalyzing many and diverse types of data. However, developing an algorithm with the aim of applying it inclinical practice is a complex task which should take into account the context in which the software is devel-oped and should be used. In the first report of the World Health Organization (WHO) about the ethics andgovernance of Artificial Intelligence (AI) for health published in 2021, it has been stated that AI may improvehealthcare and medicine all over the world only if ethics and human rights are a main part of its development.Involving ethics in technology development means to take into account several issues that should be discussedalso inside the scientific community: the epistemological changes, population stratification issues, the opacityof deep learning algorithms, data complexity and accessibility, health processes and so on. In this work, someof the mentioned issues will be discussed in order to open a discussion on whether and how it is possible to address them.

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