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Full-Text Articles in Chemicals and Drugs
Data Driven Classification Of Opioid Patients Using Machine Learning - An Investigation, Saddam Al Amin, Md Saddam Hossain Mukta, Md Sezan Mahmud Saikat, Md Ismail Hossain, Md Adnanul Islam, Mohiuddin Ahmed, Sami Azam
Data Driven Classification Of Opioid Patients Using Machine Learning - An Investigation, Saddam Al Amin, Md Saddam Hossain Mukta, Md Sezan Mahmud Saikat, Md Ismail Hossain, Md Adnanul Islam, Mohiuddin Ahmed, Sami Azam
Research outputs 2022 to 2026
The opioid crisis has led to an increased number of drug overdoses in recent years. Several approaches have been established to predict opioid prescription by health practitioners. However, due to the complex nature of the problem, the accuracy of such methods is not yet satisfactory. Dependable and reliable classification of opioid dependent patients from well-grounded data sources is essential. Majority of the previous studies do not focus on the users’ mental health association for opioid intake classification. These studies do not also employ the latest deep learning based techniques such as attention and knowledge distillation mechanism to find better insights. …
Heterogeneous Health Effects Of Medical Marijuana Legalization: Evidence From Young Adults In The United States, Junxing Chay, Seonghoon Kim
Heterogeneous Health Effects Of Medical Marijuana Legalization: Evidence From Young Adults In The United States, Junxing Chay, Seonghoon Kim
Research Collection School Of Economics
Legalizing marijuana for medical purposes is a longstanding debate. However, evidence of marijuana's health effects is limited, especially for young adults. We estimate the health impacts of medical marijuana laws (MML) in the U.S. among young adults aged 18–29 years using the difference-in-differences method and data from the Behavioral Risk Factors Surveillance System. We find that having MMLs with strict regulations generate health gains, but not in states with lax regulations. Our heterogeneity analysis results indicate that individuals with lower education attainments, with lower household income and without access to health insurance coverage gain more health benefits from MML with …