Open AccessThe development and deployment of machine learning models
Author(s) -
Pruneski James A.,
Williams Riley J.,
Nwachukwu Benedict U.,
Ramkumar Prem N.,
Kiapour Ata M.,
Martin R. Kyle,
Karlsson Jón,
Pareek Ayoosh
Publication year - 2022
Publication title -
knee surgery, sports traumatology, arthroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.806
H-Index - 125
eISSN - 1433-7347
pISSN - 0942-2056
DOI - 10.1007/s00167-022-07155-4
Subject(s) - clarity , software deployment , computer science , process (computing) , artificial intelligence , data science , work (physics) , machine learning , knowledge management , engineering , software engineering , mechanical engineering , biochemistry , chemistry , operating system
Applications of artificial intelligence, specifically machine learning, are becoming increasingly popular in Orthopaedic Surgery, and medicine as a whole. This growing interest is shared by data scientists and physicians alike. However, there is an asymmetry of understanding of the developmental process and potential applications of machine learning. As new technology will undoubtedly affect clinical practice in the coming years, it is important for physicians to understand how these processes work. The purpose of this paper is to provide clarity and a general framework for building and assessing machine learning models.