Machine Learning on 50,000 Manuscripts Shows Increased Clinical Research by Academic Cardiac Surgeons.

ABSTRACT:

Introduction

Academic cardiac surgeons are productive researchers and innovators. We sought to perform a comprehensive machine learning (ML)-based characterization of cardiac surgery research over the past 40 y to identify trends in research pursuits.

Methods

US-based academic websites were queried for surgeon profiles. Publications since 1980 were obtained from Web of Science, and publication classifications (e.g., "human", "animal") were collected through the National Institutes of Health iCite tool. Publications were deemed "basic or translational" if >50% of their classification was under "animal" or "molecular or cell", and "clinical" if otherwise. ML-based clustering was performed on publication titles and Medical Subject Heading terms to identify research topics.

R

SUBMITTER: Chandrabhatla AS 

PROVIDER: S-EPMC11602380 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature