A Decision-Support System for Diagnosing Sleep Disorders Based on the International Classification of Sleep Disorders (ICSD-III)

Introduction: Sleep disorders represent a major public health issue, significantly impacting quality of life, cognitive performance, and general well-being. Accurate diagnosis is essential for effective management; however, the complexity of sleep disorders often poses challenges for clinicians. Given the increasing use of diagnostic systems as clinical decision- support tools, we developed a computerized diagnostic system based on the International Classification of Sleep Disorders, Third Edition (ICSD-III). Methods: This system is designed to assist sleep specialists by systematically evaluating symptoms and ruling in or out potential diagnoses using a structured algorithmic approach. It is capable of diagnosing 75 distinct sleep disorders categorized into eight major groups according to the ICSD-III. The development process involved extracting disorders and their diagnostic criteria from the ICSD-III, structuring the data in an Excel database, designing the diagnostic framework using XMind software, and implementing the algorithms in Visual Studio. Results: The software was evaluated and validated by a team of sleep medicine specialists at the Occupational Sleep Research Center, Tehran University of Medical Sciences, Tehran, Iran, who confirmed its functional accuracy and consistency with ICSD-III criteria. Conclusion: This tool is intended to serve both as an educational resource and a clinical decision-support system to reduce diagnostic errors and improve efficiency. By minimizing human bias and standardizing diagnostic criteria, the software has the potential to enhance the accuracy and consistency of sleep disorder diagnosis and management. Future iterations will incorporate updates aligned with revised guidelines and may include additional features to support research and clinical applications.