Dati, algoritmi e intelligenza artificiale per il processo decisionale clinico: il futuro della medicina di laboratorio passa da qui

Abstract

Artificial intelligence (AI) is the discipline that studies whether and how computer systems capable of simulating the capacity and behavior of human thought can be created. Laboratory Medicine lends itself greatly to the development of AI applications, given the vast amount of data that it collects and archives on a daily basis, produced by analytical systems managed by increasingly sophisticated softwares. The speed with which information technologies evolve already allows the creation of complex algorithms to support the various phases of the analytical process and, probably in the future, also for diagnosis, therapy, prognosis and monitoring of the clinical course. However, if on the one hand AI applications have generated the idea that it is sufficient to have an enormous amount of data available to feed algorithms, on the other hand it has also contributed to creating, at least in part of the scientific community, confusion and distrust towards these models which sometimes appear difficult to govern. In reality, the critical capacity of human intelligence is and will always be necessary both to develop reliable models to support decisions and to contextualize and interpret data. This requires that the different professional figures involved in the development and control processes of AI systems interact and collaborate in a constant and structured way, possibly coordinated and supervised by the relevant scientific societies.

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