Classifying early infant feeding status from clinical notes using natural language processing and machine learning

Classifying early infant feeding status from clinical notes using natural language processing and machine learning

Abstract The objective of this study is to develop and evaluate natural language processing (NLP) and machine learning models to predict infant feeding status from clinical notes in the Epic electronic health records system. The primary outcome was the classification of infant feeding status from cl...

Full description

Bibliographic Details
Main Authors: Dominick J. Lemas, Xinsong Du, Masoud Rouhizadeh, Braeden Lewis, Simon Frank, Lauren Wright, Alex Spirache, Lisa Gonzalez, Ryan Cheves, Marina Magalhães, Ruben Zapata, Rahul Reddy, Ke Xu, Leslie Parker, Chris Harle, Bridget Young, Adetola Louis-Jaques, Bouri Zhang, Lindsay Thompson, William R. Hogan, François Modave
Format: Article
Language:English
Published: Nature Portfolio 2024-04-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-58299-x

Internet

https://doi.org/10.1038/s41598-024-58299-x

Similar Items