Peer-Reviewed Publication
Eur Spine J2022;31(8):2149-2155.August 1, 2022Journal Article
Performance of hybrid artificial intelligence in determining candidacy for lumbar stenosis surgery.
Raphael Mourad1,2, Serhii Kolisnyk3, Yurii Baiun4, Alessandra Falk5, Titenkov Yuriy6, Frolov Valerii6, Aleksey Kopeev6, Olga Suldina7, Andrey Pospelov5, Jack Kim5, Andrej Rusakov5, Darren R Lebl8
1University of Toulouse, CNRS, UPS, 31062, Toulouse, France. raphael.mourad@univ-tlse3.fr.
2Remedy Logic, 1177 Avenue of the Americas, 5th Floor, New York, NY, 10036, USA. raphael.mourad@univ-tlse3.fr.
3Vinnitsa National Medical University, Pyrohova St, 56, Vinnytsia, 21018, Vinnytsia Oblast, Ukraine.
4Center of Neurosurgery, Kyiv Regional Hospital, Kyiv, Ukraine.
5Remedy Logic, 1177 Avenue of the Americas, 5th Floor, New York, NY, 10036, USA.
6Federal Center of Traumatology, Orthopedics and Endoprosthetics, Cheboksary, Russia.
7Cadabra Studio, Hlinky street 2, Dnipro, 49000, Ukraine.
8Hospital for Special Surgery, 535 East 70th Street, New York, NY, 10021, USA. drlebl@stanfordalumni.org.
Abstract
PURPOSE: Lumbar spinal stenosis (LSS) is a condition affecting several hundreds of thousands of adults in the United States each year and is associated with significant economic burden. The current decision-making practice to determine surgical candidacy for LSS is often subjective and clinician specific. In this study, we hypothesize that the performance of artificial intelligence (AI) methods co…
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