# MfeCNN: Mixture Feature Embedding Convolutional Neural Network for Data Mapping

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/mfecnn-mixture-feature-embedding-convolutional-neural-network-for-data-mapping/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Dingcheng Li,Ming Huang,Xiaodi Li,Yaoping Ruan,Lixia Yao |
| Citations | 15 |
| DOI | 10.1109/tnb.2018.2841053 |
| Fields | Computer Science,Health Professions |
| Open Access | true |
| OA Status | green |
| OA URL | https://www.ncbi.nlm.nih.gov/pmc/articles/6118402 |
| OpenAlex ID | https://openalex.org/W2886875078 |
| PMID | 29993581 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Xiaodi Li](https://scholariq.org/researchers/xiaodi-li/)

## Paper primary topic

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)

## Paper topics

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-in-healthcare/)

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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.