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Editor-in-chief
Maria Stella Graziani

Deputy Director
Martina Zaninotto

Associate Editors
Ferruccio Ceriotti
Davide Giavarina
Bruna Lo Sasso
Giampaolo Merlini
Martina Montagnana
Andrea Mosca
Paola Pezzati
Rossella Tomaiuolo
Matteo Vidali

International Advisory Board Khosrow Adeli Canada
Sergio Bernardini Italy
Marcello Ciaccio Italy
Eleftherios Diamandis Canada
Philippe Gillery France
Kjell Grankvist Sweden
Hans Jacobs The Netherlands
Eric Kilpatrick UK
Magdalena Krintus Poland
Giuseppe Lippi Italy
Mario Plebani Italy
Sverre Sandberg Norway
Ana-Maria Simundic Croatia
Tommaso Trenti Italy
Cas Weykamp The Netherlands
Maria Willrich USA
Paul Yip Canada


Publisher
Biomedia srl
Via L. Temolo 4, 20126 Milano

Responsible Editor
Giuseppe Agosta

Editorial Secretary
Andrea di Bello
Biomedia srl
Via L. Temolo 4, 20126 Milano
Tel. 0245498282
email: biochimica.clinica@sibioc.it

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ISSN print: 0393 – 0564
ISSN digital: 0392- 7091



Articoli con TAG: intelligenza artificiale

Introduzione ai Big Data e all’Intelligenza Artificiale in Medicina di Laboratorio
Introduction to Big Data and Artificial Intelligence in Laboratory Medicine
<p>Currently, thanks to the growing computing capacity and the increasing availability of digital data, Data Science is playing an important role in the future development of Laboratory Medicine. However, the concepts of Big Data (BD) and Artificial Intelligence (AI) can still be interpreted in various ways. Clinical laboratories are certainly among the health care organizations producing an important number of data that can be considered BD and it is certainly not a coincidence that they are among the first health organizations to have implemented computer systems within their workflows. Through a process called Data Mining it is possible to extract useful information from BD using automatic or semi-automatic methods that must be preceded by Data Cleaning in order to ensure the cleanliness and correctness of the data themself. Regarding Data Analysis, several Machine Learning or Deep Learning techniques based on different algorithms or on the functioning principle of neural networks can be used; for the development of these techniques, R and Python programming languages are really useful. Although many applications can be useful in Laboratory Medicine, there are still some obstacles to overcome, including poor harmonization of data or fragmentation of sources; moreover, the issue of data accessibility must be managed considering patient&rsquo;s privacy as a priority. Finally, there is an increase apprehension related to the awareness of the inevitable innovation in the Laboratory Medicine field in the near future, because of these new approaches. To face these challenges, it is necessary that these topics become familiar to the professionals of Laboratory Medicine. Aim of this Document is to share information about BD and AI in order to contribute to the introduction and development of these methodologies in the field of Laboratory Medicine.</p>
Biochimica Clinica ; 45(1) 057-067
Documenti - Documents