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B. Bigliardi, V. Bellini, E.G. Bignami, A. Petroni

University of Parma (ITALY)
Artificial intelligence (AI) in general and machine learning (ML) algorithms in particular, is a branch in computer science that is rapidly gaining importance within the healthcare sector [1; 2]. Indeed, a search on PubMed with the keyword "machine learning" shows that the number of papers published on the topic has increased since the beginning of this decade: more than 4.000 papers have been published in the last 10 years.

Specifically, both recent regulatory approvals and research agree in stating that these tools could play a key role by defining the way medicine will be practiced [3]. Thus, research stress that medical education and other teaching programs are required within academic teaching hospitals on the technology of AI and ML [4].

This paper aims at investigating the role of ML in the healthcare sector, and at demonstrating that educating the next generation of medical professionals with the right ML techniques will enable them to become part of this emerging revolution.

[1] Z. Obermeyer and E.J. Emanuel, “Predicting the future - big data, machine learning, and clinical medicine”, N. Engl. J. Med., vol. 375, pp. 1216–1219, 2016.
[2] A. Darcy, A.K. Louie and L.W. Roberts, “Machine learning and the profession of medicine”, JAMA, vol. 315, pp. 551–552, 2016.
[3] A.L Beam and I.S. Kohane, “Big data and machine learning in health care”, JAMA, (2018).
[4] V.B. Kolachalama and P.S. Garg, “Machine learning and medical education”, NPJ Digital Medicine, vol. 1, no. 1, pp. 54, 2018.