RA V-Net: deep learning network for automated liver segmentation.

Segmenting liver from CT images is the first step for doctors to diagnose a patient's disease. Processing medical images with deep learning models has become a current research trend. Although it can automate segmenting region of interest of medical images, the inability to achieve the required segmentation accuracy is an urgent problem to be solved.

WVMDA: Predicting miRNA-Disease Association Based on Weighted Voting.

An increasing number of experiments had verified that miRNA expression is related to human diseases. The miRNA expression profile may be an indicator of clinical diagnosis and provides a new direction for the prevention and treatment of complex diseases. In this work, we present a weighted voting-based model for predicting miRNA-disease association (WVMDA).