Intelligent algorithm based on deep learning to predict the dosage for anesthesia: A study on prediction of drug efficacy based on deep learning.

Background And Aims: Anesthetic drugs play a vital role during surgery, however, due to individual differences and complex physiological mechanisms, the prediction of anesthetic drug dosage has always been a challenging problem. In this study, we propose a model for predicting the dosage of anesthetic drugs based on deep learning to help anesthesiologists better control their dosage during surgical procedures.

Methods: We design a model based on the artificial neural network to predict the dosage of preoperative anesthetic, and use the SELU activation function and the loss function for weighted regularization to solve the problem of unbalanced sample.

Retracted Article: LncRNA OIP5-AS1 contributes to ox-LDL-induced inflammation and oxidative stress through regulating the miR-128-3p/CDKN2A axis in macrophages.

Long non-coding RNA OIP5-AS1 (lncRNA OIP5-AS1) and microRNA-128-3p (miRNA-128-3p) have been reported to play significant roles in human diseases. However, their role in atherosclerosis (AS) has been less studied. The aim of this research was to reveal the roles and functional mechanisms of OIP5-AS1 and miRNA-128-3p in AS development.