Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends-Reference-Cited by-同舟云学术

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Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends

Published:2024-04 Issue:7 Volume:10 Page:e29050
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Ghanem Marc^ORCID,Espinosa Camilo,Chung Philip,Reincke Momsen,Harrison Natasha,Phongpreecha Thanaphong,Shome Sayane,Saarunya Geetha,Berson Eloise,James Tomin,Xie Feng,Shu Chi-Hung,Hazra Debapriya,Mataraso Samson,Kim Yeasul,Seong David,Chakraborty Dipro,Studer Manuel,Xue Lei,Marić Ivana,Chang Alan L.,Tjoa Erico^ORCID,Gaudillière Brice,Tawfik Vivianne L.,Mackey Sean,Aghaeepour Nima

Funder

Bill & Melinda Gates Foundation

NIGMS

Publisher

Elsevier BV

Reference57 articles.

1. National Institutes of health–funded anesthesiology research and anesthesiology Physician-Scientists;Chandrakantan;Anesth. Analg.,2019

2. Trends in anesthesiology research: a machine learning approach to theme discovery and summarization;Rusanov;JAMIA Open,2018

3. X. Song, Topic Modeling for Natural Language Understanding, (n.d.). https://doi.org/10.17918/etd-7143..

4. Applications of Topic Models;Boyd-Graber,2017

5. Data clustering using unsupervised machine learning;Chander;Statistical Modeling in Machine Learning,2023

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