Comparative Analysis of Deep Learning Techniques for Drug Addiction

Substances that alter a person’s mental or physical state are referred to as drugs. They have the ability to alter how your brain functions, how you feel and behave, your understanding, and your senses. As a result, they are unpredictably dangerous, especially to children. Drug abuse has a startling annual death toll of 11.8 million people, which has a significant impact on the mortality rate around the world. The situation is becoming worse by the fact that substance addiction frequently sets off the signs of mental health conditions. Addiction analysis has been used to promote awareness and rehabilitate from addiction. Existing Machine Learning for drug analysis is mostly based on Machine learning techniques. In this paper, we used Deep Learning techniques to overcome the limitations of the existing Machine learning models. Here the Zenodo Dataset is used which is collected from social media like Reddit. It contains a total of 3151 tweets related to drug addiction.