Predictive Scheduling and Throughput Optimisation in Outpatient Clinical Workflows: Machine Learning Models for Ambulatory Care Efficiency

Authors

  • Ana Castaño Associate Professor of Computer Science, University of Buenos Aires

Keywords:

predictive scheduling, throughput optimisation, outpatient clinical workflows, machine learning models, ambulatory care efficiency

Abstract

Machine Learning Approaches for Improving Patient Flow and Efficiency in Ambulatory Care: AI Models for Streamlining Scheduling and Reducing Wait Times The value and importance of healthcare services are realized through care delivery; therefore, it is vital to seek innovations for increasing operational efficiency and patient access to care. Artificial intelligence (AI) provides a way to achieve this endeavor.

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Published

30-06-2026

How to Cite

[1]
“Predictive Scheduling and Throughput Optimisation in Outpatient Clinical Workflows: Machine Learning Models for Ambulatory Care Efficiency”, Adv. in Deep Learning Techniques, vol. 6, no. 1, pp. 1–9, Jun. 2026, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/adlt/article/view/776