INFORMATION AND ANALYTICAL SYSTEM FOR ASSESSING THE HEALTH STATUS OF STUDENTS

The purpose of our work was to study the effectiveness using an intelligent information- analytical system assess health status students on basis one universities in Kazakhstan, Kazakh National University named after Al -Farabi. For this purpose, a simulation performed individual data 4456 university students. involved 47.4% female and 52.6% males; predominant age ranged from 18 21 years (66.9%), distribution by almost uniform. classification were used such as Vector Machine, K - Nearest Neighbour, Random Forest Naive Bayes supports. performance metrics chosen evaluate use various prediction algorithms Specifity, Sensitivity, Accuracy, Accessibility. It has been established that when classifier Support Machine ’s Accessibility scores are at their highest, reaching 97%. overall developed information evaluated Reliability parameter. In comparison with other well-known systems for monitoring patients (AmbIGEM AAL ), us showed higher reliability (90-95%). future, model can be expand including external parameters also affect addition, it is planned introduce Deep Learning monitor educational institutions Kazakhstan world.