Computational Aspects and Statistical Models in Sleeping Disorders; an Apriori Algorithm Approach

Document Type : Original Article


1 Department of Computer Science, ITM (SLS) Baroda University, Vadodara, India

2 DANA Brain Health Institute, Iranian Neuroscience Society-Fars Chapter, Shiraz, Iran

3 Students' Research Committee, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

4 Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran

5 Provost, Techno India JNR, Institute of Technology, Udaipur 313003, Rajasthan, India

6 Neuroscience Center, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama City, Republic of Panama


Sleep disorders are very common in today’s world as we all are living a relatively competitive life; where we undervalue our mental health. There are some sleep disorders that share almost similar symptoms yet various pathological underpinnings leading to clinical misjudgments; thereby resulting in the inappropriate treatments. The present study has attempted to investigate possible correlation between various types of sleep predicaments. To do so; we used multiple statistical analysis algorithms as well as prediction models on our database and performed manual testing to draw our conclusion. Our analyses revealed that sleep disorders; and namely sleep apnea-hypopnea syndrome; tend to present with related comorbidities