Convolutional Neural Network and Bidirectional Long Short-Term Memory-Based Method for Predicting Drug–Disease Associations
Identifying novel indications for approved drugs can accelerate drug development and reduce research costs. Most previous studies used shallow models for prioritizing the potential drug-related diseases and failed to deeply integrate the paths between drugs and diseases which may contain additional...
Main Authors: | Ping Xuan, Yilin Ye, Tiangang Zhang, Lianfeng Zhao, Chang Sun |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-07-01
|
Series: | Cells |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4409/8/7/705 |
Similar Items
-
Convolution Neural Network Bidirectional Long Short-Term Memory for Heartbeat Arrhythmia Classification
by: Rami S. Alkhawaldeh, et al.
Published: (2023-12-01) -
Assistant diagnosis with Chinese electronic medical records based on CNN and BiLSTM with phrase-level and word-level attentions
by: Tong Wang, et al.
Published: (2020-06-01) -
A text classification method based on a convolutional and bidirectional long short-term memory model
by: Hai Huan, et al.
Published: (2022-12-01) -
Emergency sign language recognition from variant of convolutional neural network (CNN) and long short term memory (LSTM) models
by: Muhammad Amir As'ari, et al.
Published: (2024-02-01) -
Research on Emotion Analysis and Psychoanalysis Application With Convolutional Neural Network and Bidirectional Long Short-Term Memory
by: Baitao Liu
Published: (2022-06-01)