In the last few years, artificial intelligence (AI) is gaining attention in several medical disciplines, including laboratorymedicine (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 importantpart of the routine workflow of patients' data. Motivated by these topics and under the auspices of SIBioC, a conferenceon AI and big data was organized in May 2022 in Bologna, Italy. This conference covered several topics of AI and bigdata, including but not limited to the current and future perspectives, comprising ethical challenges and the role oflaboratory specialists, including young professionals, the productive integration of AI with information technologies andwith other digital infrastructure, such as the LOINC and the block chain. Furthermore, some examples of real applicationof AI in LM were reported, including diagnosis and monitoring of familiar hypercholesterolemia, management of insulintreatments for diabetes, reference intervals identification and verification by indirect methods, COVID-19 diagnosisand the monitoring of outpatients monoclonal gammopathy treatment by digital healthcare.
Big Data e Intelligenza Artificiale in Medicina di Laboratorio
M Ciampi;M T Chiaravalloti;
2022
Abstract
In the last few years, artificial intelligence (AI) is gaining attention in several medical disciplines, including laboratorymedicine (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 importantpart of the routine workflow of patients' data. Motivated by these topics and under the auspices of SIBioC, a conferenceon AI and big data was organized in May 2022 in Bologna, Italy. This conference covered several topics of AI and bigdata, including but not limited to the current and future perspectives, comprising ethical challenges and the role oflaboratory specialists, including young professionals, the productive integration of AI with information technologies andwith other digital infrastructure, such as the LOINC and the block chain. Furthermore, some examples of real applicationof AI in LM were reported, including diagnosis and monitoring of familiar hypercholesterolemia, management of insulintreatments for diabetes, reference intervals identification and verification by indirect methods, COVID-19 diagnosisand the monitoring of outpatients monoclonal gammopathy treatment by digital healthcare.File | Dimensione | Formato | |
---|---|---|---|
prod_489597-doc_203901.pdf
accesso aperto
Descrizione: Big Data e Intelligenza Artificiale in Medicina di Laboratorio
Tipologia:
Versione Editoriale (PDF)
Licenza:
Creative commons
Dimensione
268.63 kB
Formato
Adobe PDF
|
268.63 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.