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Alcoholism is an unhealthy lifestyle associated with alcohol dependence. Not only does drinking for a long time leads to poor mental health and loss of self-control, but alcohol seeps into the bloodstream and shortens the lifespan of the body’s internal organs. Alcoholics often think of alcohol as an everyday drink and see it as a way to reduce stress in their lives because they cannot see the damage in their bodies and they believe it does not affect their physical health. As their drinking increases, they become dependent on alcohol and it affects their daily lives. Therefore, it is important to recognize the dangers of alcohol abuse and to stop drinking as soon as possible. To assist physicians in the diagnosis of patients with alcoholism, we provide a novel alcohol detection system by extracting image features of wavelet energy entropy from magnetic resonance imaging (MRI) combined with a linear regression classifier. Compared with the latest method, the 10-fold cross-validation experiment showed excellent results, including sensitivity    91  .  54  ±  1  .  47  %   , specificity    93  .  66  ±  1  .  34  %   , Precision    93  .  45  ±  1  .  27  %   , accuracy    92  .  61  ±  0  .  81  %   , F1 score    92  .  48  ±  0  .  83  %    and MCC    85  .  26  ±  1  .  62  %   .

Alcoholism Detection by Wavelet Energy Entropy and Linear Regression Classifier