# Graph Convolutional Autoencoder and Fully-Connected Autoencoder with Attention Mechanism Based Method for Predicting Drug-Disease Associations

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/graph-convolutional-autoencoder-and-fully-connected-autoencoder-with-attention/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ping Xuan,Ling Gao,Nan Sheng,Tiangang Zhang,Toshiya Nakaguchi |
| Citations | 61 |
| DOI | 10.1109/jbhi.2020.3039502 |
| Fields | Biochemistry, Genetics and Molecular Biology,Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3106165797 |
| PMID | 33216722 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Toshiya Nakaguchi](https://scholariq.org/researchers/toshiya-nakaguchi/)

## Paper journal

- [IEEE Journal of Biomedical and Health Informatics](https://scholariq.org/journals/ieee-journal-of-biomedical-and-health-informatics/)

## Paper primary topic

- [Computational Drug Discovery Methods](https://scholariq.org/topics/computational-drug-discovery-methods/)

## Paper topics

- [Computational Drug Discovery Methods](https://scholariq.org/topics/computational-drug-discovery-methods/)
- [Bioinformatics and Genomic Networks](https://scholariq.org/topics/bioinformatics-and-genomic-networks/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.