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Brain scanners are used to detect brain activity with the help of neuro symptoms, which help to obtain specific functions or mental disorders. On top of for years doctors have used traditional questions and observation techniques to find out to diagnose individuals affected by mental illness, however, there is a long trial as well error process. With the introduction of MRI and other forms of brain scans, it became easier for doctors to monitor brain function and response to other stimuli and record responses. This paper aims to better understand and by using image processing techniques, you can see these problems and reactions to understand how the brain responds and allow doctors to act better and more accurately diagnose mental illness. Various classification algorithms like Logistic Regression (LR), Random Forest (RF), Decision Tree (TR), KNN, Super Vector Machine (SVM), and NAÏVE BAYES (NB) are used for bipolar disorder and evaluating accuracy.