In the last few years, artificial intelligence (AI) is gaining attention in several medical disciplines, including laboratory medicine (LM). The raised interest on AI has been fueled not only by the huge amounts of information daily generated, but also by the special natural context offered by laboratories, where digitalization have already occupied an important part of the routine workflow of patients’ data. Motivated by these topics and under the auspices of SIBioC, a conference on AI and big data was organized in May 2022 in Bologna, Italy. This conference covered several topics of AI and big data, including but not limited to the current and future perspectives, comprising ethical challenges and the role of laboratory specialists, including young professionals, the productive integration of AI with information technologies and with other digital infrastructure, such as the LOINC and the block chain. Furthermore, some examples of real application of AI in LM were reported, including diagnosis and monitoring of familiar hypercholesterolemia, management of insulin treatments for diabetes, reference intervals identification and verification by indirect methods, COVID-19 diagnosis and the monitoring of outpatients monoclonal gammopathy treatment by digital healthcare.

Big Data e Intelligenza Artificiale in Medicina di Laboratorio

Elena Stanghellini
2022

Abstract

In the last few years, artificial intelligence (AI) is gaining attention in several medical disciplines, including laboratory medicine (LM). The raised interest on AI has been fueled not only by the huge amounts of information daily generated, but also by the special natural context offered by laboratories, where digitalization have already occupied an important part of the routine workflow of patients’ data. Motivated by these topics and under the auspices of SIBioC, a conference on AI and big data was organized in May 2022 in Bologna, Italy. This conference covered several topics of AI and big data, including but not limited to the current and future perspectives, comprising ethical challenges and the role of laboratory specialists, including young professionals, the productive integration of AI with information technologies and with other digital infrastructure, such as the LOINC and the block chain. Furthermore, some examples of real application of AI in LM were reported, including diagnosis and monitoring of familiar hypercholesterolemia, management of insulin treatments for diabetes, reference intervals identification and verification by indirect methods, COVID-19 diagnosis and the monitoring of outpatients monoclonal gammopathy treatment by digital healthcare.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1552473
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