Machine learning and conventional statistics: making sense of the differences

Autor:	Christophe Ley, R. Kyle Martin, Ayoosh Pareek, Andreas Groll, Romain Seil, Thomas Tischer
Rok vydání:	2022
Předmět:	Machine Learning Orthopedics Orthopédie rééducation & médecine sportive [D17] [Sciences de la santé humaine] Humans Orthopedics and Sports Medicine Surgery Orthopedics rehabilitation & sports medicine [D17] [Human health sciences]
Zdroj:	Knee Surgery, Sports Traumatology, Arthroscopy. 30:753-757
ISSN:	1433-7347 0942-2056
Popis:	The application of machine learning (ML) to the field of orthopaedic surgery is rapidly increasing, but many surgeons remain unfamiliar with the nuances of this novel technique. With this editorial, we address a fundamental topic-the differences between ML techniques and traditional statistics. By doing so, we aim to further familiarize the reader with the new opportunities available thanks to the ML approach.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d0e512e9d250a2899c79a89198425b0 https://doi.org/10.1007/s00167-022-06896-6 Zobrazit plný text záznamu Full text from SpringerLink Plný text