Machine learning models can predict subsequent publication of North American Spine Society (NASS) annual general meeting abstracts.

ABSTRACT:

Background context

Academic meetings serve as an opportunity to present and discuss novel ideas. Previous studies have identified factors predictive of publication without generating predictive models. Machine learning (ML) presents a novel tool capable of generating these models. As such, the objective of this study was to use ML models to predict subsequent publication of abstracts presented at a major surgical conference.

Study design/setting

Database study.

Methods

All abstracts from the North American Spine Society (NASS) annual general meetings (AGM) from 2013-2015 were reviewed. The following information was extracted: number of authors, institution, location, conference category, subject category, study type, data collection methodology, human subject research

SUBMITTER: Abbas A 

PROVIDER: S-EPMC10443859 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature