# GP-CNN-DTEL: Global-Part CNN Model With Data-Transformed Ensemble Learning for Skin Lesion Classification

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/gp-cnn-dtel-global-part-cnn-model-with-data-transformed-ensemble-learning-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Peng Tang,Qiaokang Liang,Xintong Yan,Shao Xiang,Dan Zhang |
| Citations | 135 |
| DOI | 10.1109/jbhi.2020.2977013 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3008320599 |
| PMID | 32142460 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Qiaokang Liang](https://scholariq.org/researchers/qiaokang-liang/)
- [Shao Xiang](https://scholariq.org/researchers/shao-xiang/)

## Paper journal

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

## Paper primary topic

- [Cutaneous Melanoma Detection and Management](https://scholariq.org/topics/cutaneous-melanoma-detection-and-management/)

## Paper topics

- [Cutaneous Melanoma Detection and Management](https://scholariq.org/topics/cutaneous-melanoma-detection-and-management/)
- [Nonmelanoma Skin Cancer Studies](https://scholariq.org/topics/nonmelanoma-skin-cancer-studies/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

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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.