Applying Machine Learning Algorithms for the Classification of Sleep Disorders

Applying Machine Learning Algorithms for the Classification of Sleep Disorders

   Duvvala Ajay1, Botla Prem kumar2, Challa VivekVardhan3,Viswajeet Murmu4, Mr.J.N ChandraSekhar4

1,2,3, UG Scholars, 4Assistant Professor

1,2,3,4 Department of Artificial Intelligence & DataScienc,

  1,2,3,4 Guru Nanak Institutions Technical Campus, Hyderabad, Telangana, India

Abstract - People's health and well-being are greatly impacted by sleep disorders, including insomnia, sleep apnea, and other conditions. The quality of life for those impacted by these disorders can be improved by early diagnosis and efficient treatment made possible by accurate and efficient classification.
people. For classification, the majority of the current systems use Artificial Neural Networks (ANN), which are efficient but sometimes computationally demanding and difficult to understand. This study uses a dataset of 400 samples with 13 pertinent features to propose a Random Forest-based method for classifying sleep disorders. Because of its superior capacity to manage intricate, non-linear relationships within the data, as well as its robustness and interpretability, the Random Forest model was chosen..[2]

Key Words: Sleep Issues,Sleeplessness,Apnea in Sleep,Classification of Sleep Disorders