Detection of ADHD and Explaining the Factors

In today’s world, ADHD is one of the most unnoticed problems in society. This is often undetected and as a result, left undiagnosed. But, this should not be the case, as it has some serious effects on our lives. Not only in the life of the individual carrying the disorder but people surrounding them can also get affected by them, as lack of attention is there, and as a result, the individual faces anger issues and may be harmful to the society. Firstly, we tried to detect ADHD with EEG brain recording data of ADHD and non-ADHD individuals using a machine learning classification algorithm. In addition, we tried to explain the reason of a prediction, which means how a prediction is made in the way it is made. What attributes contributed in the prediction and in what manner is explained in this work. This study was successful in the prediction task of ADHD with an accuracy of 97% and also getting some insights to the prediction by the use of explainable AI algorithms like LIME and SHAP.