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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Detalles Bibliográficos
Autores principales: Zhou, Shang-Ming, Lyons, Ronan A., Rahman, Muhammad A., Holborow, Alexander, Brophy, Sinead
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779953/
https://www.ncbi.nlm.nih.gov/pubmed/35055401
http://dx.doi.org/10.3390/jpm12010086

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8779953/
https://www.ncbi.nlm.nih.gov/pubmed/35055401
http://dx.doi.org/10.3390/jpm12010086

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