Background No-show to medical appointments has significant adverse effects on healthcare
systems and their clients. Using machine learning to predict no-shows allows managers to …

Appointment scheduling is critical to increasing resource utilization and operational
performance in various industry domains, especially healthcare. Costs to care for several …

Hospitals that are considered non-profit take into consideration not to make any losses other
than seeking profit. A model that ensures that hospital price policies are variable due to …

Artificial Intelligence (AI) refers to the development of computer systems that can perform
tasks that typically require human intelligence. The utilization of AI in healthcare, particularly …

Timely pre-and post-diagnosis check-ups are critical for various diseases, in general, and for
cancer, in particular, as these often lead to better outcomes. Several socio-demographic …

This study addresses patient unpunctuality, a major concern affecting patient waiting time,
resource utilization, and quality of care. We develop and compare four machine learning …

Healthcare systems face significant challenges and financial burdens due to patient no-
shows, highlighting the need for accurate and interpretable predictive models. This study …

Applications of several exponentially weighted moving average (EWMA) schemes for
monitoring binomial count data have been widely used in the manufacturing and healthcare …

Background Primary health care (PHC) services face operational challenges due to high
patient volumes, leading to complex management needs. Patients access services through …

Timely pre-and post-diagnosis check-ups are critical for cancer patients, across all cancer
types, as these often lead to better outcomes. Several socio-demographic properties have …