The race to make the dream of artificial intelligence a reality comes parallel with the increasing struggle of health care systems to cope with information overload and translational pressure. It is clear that a shift in the way data is generated requires a shift in the way they are processed. This is where AI comes with great promises to solve the problem of volume versus applicability of information in science. In medicine, AI is showing exponential progress in the fields of predictive analysis and image recognition. These promises however, come with an intricate package of ethico-social, scientific and economic implications, towards which a reductionist approach leads to distorted and dramatic predictions. All this, in a time when the growing pressure on healthcare systems towards defensive medicine begs the question of the true need for AI for good medical practice.This article examines the concept and achievements of AI and attempts to offer a complex view on the realistic expectations from it in medicine, in the context of current practice (Ref. 38). Keywords: algorithms, artificial intelligence, image recognition, neural networks, predictive analysis.
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http://dx.doi.org/10.4149/BLL_2019_028 | DOI Listing |
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