Predicting ophthalmic clinic non‐attendance using machine learning: Development and validation of models using nationwide data
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Title
Predicting ophthalmic clinic non‐attendance using machine learning: Development and validation of models using nationwide data
Authors
Keywords
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Journal
CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY
Volume -, Issue -, Pages -
Publisher
Wiley
Online
2023-10-27
DOI
10.1111/ceo.14310
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Related references
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- (2022) Dianbo Liu et al. npj Digital Medicine
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- (2020) Michael Green et al. AMERICAN JOURNAL OF OPHTHALMOLOGY
- Patient No-Show Prediction: A Systematic Literature Review
- (2020) Danae Carreras-García et al. Entropy
- The Relationship of Travel Distance to Postoperative Follow-up Care on Glaucoma Surgery Outcomes
- (2020) Ian T. Funk et al. JOURNAL OF GLAUCOMA
- Evaluating the Impact of Patient No-Shows on Service Quality
- (2020) Dounia Marbouh et al. Risk Management and Healthcare Policy
- Development and validation of a patient no-show predictive model at a primary care setting in Southern Brazil
- (2019) Henry Lenzi et al. PLoS One
- Machine Learning in Epidemiology and Health Outcomes Research
- (2019) Timothy L. Wiemken et al. Annual Review of Public Health
- Global prevalence of amblyopia and disease burden projections through 2040: a systematic review and meta-analysis
- (2019) Zhujun Fu et al. BRITISH JOURNAL OF OPHTHALMOLOGY
- Using machine-learning approaches to predict non-participation in a nationwide general health check-up scheme
- (2018) Akihiro Shimoda et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- No-shows in appointment scheduling – a systematic literature review
- (2018) Leila F. Dantas et al. HEALTH POLICY
- Treat-and-Extend versus Monthly Regimen in Neovascular Age-Related Macular Degeneration
- (2018) Rufino Silva et al. OPHTHALMOLOGY
- The Impact of mHealth Interventions: Systematic Review of Systematic Reviews
- (2018) Milena Soriano Marcolino et al. JMIR mHealth and uHealth
- Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data
- (2018) Milena A. Gianfrancesco et al. JAMA Internal Medicine
- Outpatient appointment systems in healthcare: A review of optimization studies
- (2017) Amir Ahmadi-Javid et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Childhood amblyopia: current management and new trends
- (2016) Vijay Tailor et al. BRITISH MEDICAL BULLETIN
- Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement
- (2015) G. S. Collins et al. BRITISH JOURNAL OF SURGERY
- An educational intervention to improve adherence to high-dosage patching regimen for amblyopia: a randomised controlled trial
- (2014) Archana Pradeep et al. BRITISH JOURNAL OF OPHTHALMOLOGY
- Panel Size and Overbooking Decisions for Appointment-Based Services under Patient No-Shows
- (2014) Nan Liu et al. PRODUCTION AND OPERATIONS MANAGEMENT
- Appointment Overbooking in Health Care Clinics to Improve Patient Service and Clinic Performance
- (2012) Linda R. LaGanga et al. PRODUCTION AND OPERATIONS MANAGEMENT
- Screening Uptake in a Well-Established Diabetic Retinopathy Screening Program: The role of geographical access and deprivation
- (2008) G. P. Leese et al. DIABETES CARE
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