Machine learning –based outcome prediction and novel hypotheses generation for substance use disorder treatment

ConclusionsWe identified new interaction effects among the length of stay, frequency of substance use, changes in self-help group attendance frequency, and other factors. This work provides insights into the interactions between factors impacting treatment completion. Further traditional statistical analysis can be employed by practitioners and policy makers to test the effects discovered by our novel machine learning approach.
Source: Journal of the American Medical Informatics Association - Category: Information Technology Source Type: research