Study Results from College of Computer Science and Engineering Provide New Insights into Sleep Disorders (Applying Machine Learning Algorithms for the Classification of Sleep Disorders).

A study conducted by the College of Computer Science and Engineering explores the use of machine learning algorithms (MLAs) for the classification of sleep disorders. The study compares deep learning algorithms and conventional MLAs and proposes an optimized method for sleep disorder classification. The results show that the artificial neural network (ANN) algorithm achieved the highest classification accuracy of 92.92%. This research provides valuable insights into the potential of MLAs in improving the accuracy of sleep disorder classification, which can have a significant impact on human health and quality of life. [Extracted from the article]