… list of predicted drug combinations involving non-hypertensive drugs with Complementary
… Finally, given the lack of large-scale, systematic data on combinations of multiple drugs, in …

… extraction method of DDI and the prediction method of DDI. We first … prediction models.
Finally, we discuss the challenges and prospects of machine learning methods in predicting drug …

… Empirical results on three biomedical knowledge graphs of different scales show that … -label
DDI prediction task and further studies verify the efficacy of both probability-based sampling …

… personal substance use predicts relapse after inpatient SUD treatment for illicit drug use, after
… (eg age, education) and treatment variables (eg length of stay, treatment completion). We …

… in large-scale neural networks contribute to variability in treatment outcomes for cocaine …
Despite advances in substance use treatment, the effectiveness of most interventions remains …

… alcohol use indicative of dependence based … different scale. Individual alpha diversity metrics
were reverse scored according to theory prior to being converted into a standardized scale. …

… At the time of treatment admission, a chronological history of alcohol use was collected by a
… Our results indicate that elevated scores on a self-reported craving scale (PACS) at the time …

… in emotional and personality-based variables in predicting virus-mitigating behaviors. … using
politics and moral orientation and then additionally FCV-19S and PROMIS scales to predict …

… Next, we discuss the knowledge graph completion methods that we used to predict candidate
drugs … multi-objective loss function then is: L = L c + γ L d where γ is a scaling factor for the …

… We found that deepDR revealed high performance in predicting drug–disease associations
… Although our sizeable efforts assembled large-scale, experimentally reported drug–target …