Predicting Hospital Readmission for Campylobacteriosis from Electronic Health Records: A Machine Learning and Text Mining Perspective

Predicting Hospital Readmission for Campylobacteriosis from Electronic Health Records: A Machine Learning and Text Mining Perspective

(1) Background: This study investigates influential risk factors for predicting 30-day readmission to hospital for Campylobacter infections (CI). (2) Methods: We linked general practitioner and hospital admission records of 13,006 patients with CI in Wales (1990–2015). An approach called TF-zR (term...

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Bibliographic Details
Main Authors: Shang-Ming Zhou, Ronan A. Lyons, Muhammad A. Rahman, Alexander Holborow, Sinead Brophy
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Journal of Personalized Medicine
Subjects:
hospitalisation
readmission
<i>Campylobacter</i> infections
machine learning
text mining
feature selection
Online Access:https://www.mdpi.com/2075-4426/12/1/86

Internet

https://www.mdpi.com/2075-4426/12/1/86

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