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Predicting Psychedelic Experience Outcomes Through Machine Learning
The results paves the way for psychedelic research to incorporate more machine learning techniques.
New research has applied machine learning to predict the outcomes of psychedelic experiences to treat addiction.
The study, published in The American Journal of Drug and Alcohol Abuse, found that the machine learning algorithm could significantly predict whether a participant was able to quit or reduce their substance use, purely based on the written report of the psychedelic experience.
Psychedelics for Substance Abuse
This research, led by David Cox and colleagues from Johns Hopkins University, comes off the back of evidence that psychedelic substances may be used to treat addiction. Academic efforts in the ’60s established that LSD may have anti-addictive properties in the context of alcoholism. And, more recently, a study revealed that psilocybin, the psychoactive component in magic mushrooms, could help smokers quit. However, while there is increasing evidence that psychedelics may be useful in the fight against addiction, researchers are still unsure as to why it is effective.
