Machine Learning (ML) is a field of Scientific Computing that emerged in the last decades to investigate complex phenomena based on huge amounts of observational data. In the context of Biomedicine, an increasing body of literature makes use of ML based approaches as an alternative to standard statistical inference. Moreover, a number of studies are now focusing on adopting ML to disclose new results that otherwise would have not been possible to achieve with classical inference. In this short review we outline fundamentals of ML, by further providing examples gathered from scientific literature to highlight the potentialities of ML for clinical purposes.
ON MACHINE LEARNING IN BIOMEDICINE
Alessandro Calamuneri;Luigi Donato;Concetta Scimone;Alessandra Costa;Rosalia D’Angelo;Antonina Sidoti
2017-01-01
Abstract
Machine Learning (ML) is a field of Scientific Computing that emerged in the last decades to investigate complex phenomena based on huge amounts of observational data. In the context of Biomedicine, an increasing body of literature makes use of ML based approaches as an alternative to standard statistical inference. Moreover, a number of studies are now focusing on adopting ML to disclose new results that otherwise would have not been possible to achieve with classical inference. In this short review we outline fundamentals of ML, by further providing examples gathered from scientific literature to highlight the potentialities of ML for clinical purposes.Pubblicazioni consigliate
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