Using machine learning tools to investigate factors associated with trends in ‘no-shows’ in outpatient appointments-Reference-Cited by-同舟云学术

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Using machine learning tools to investigate factors associated with trends in ‘no-shows’ in outpatient appointments

Published:2021-01 Issue: Volume:67 Page:102496
ISSN:1353-8292
Container-title:Health & Place
language:en
Short-container-title:Health & Place

Author:

Incze Eduard^ORCID,Holborn Penny,Higgs Gary,Ware Andrew

Funder

ESF

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Geography, Planning and Development,Health(social science)

Reference61 articles.

1. Artificial Intelligence in Healthcare;Academy of Royal Medical Colleges,2019

2. Benchmarking And Optimization Of Gradient Boosting Decision Tree Algorithms, Workshop on Systems for ML and Open;Anghel,2018

3. The economics of non-attendance and the expected effect of charging a fine on non-attendees;Bech;Health Pol.,2005

4. Principles of Data Mining;Bramer,2007

5. Arcing the edge;Breiman;Ann. Probab.,1998

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1. Dynamic Price Application to Prevent Financial Losses to Hospitals Based on Machine Learning Algorithms;Healthcare;2024-06-26

2. Predicting the probabilities of missed general practice appointments in England and Wales;2024-01-10

3. Decision analysis framework for predicting no-shows to appointments using machine learning algorithms;BMC Health Services Research;2024-01-05

4. Attendance at remote versus in-person outpatient appointments in an NHS Trust;Journal of Telemedicine and Telecare;2023-12-21

5. Attendance at remote versus face-to-face outpatient appointments in an NHS Trust;2023-09-26

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