# Improved multi-classification of breast cancer histopathological images using handcrafted features and deep neural network (dense layer)

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/improved-multi-classification-of-breast-cancer-histopathological-images-using/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Agaba Ameh Joseph,Mohammed Abdullahi,Sahalu B. Junaidu,Hayatu Hassan Ibrahim,Haruna Chiroma |
| Citations | 105 |
| DOI | 10.1016/j.iswa.2022.200066 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.sciencedirect.com/science/article/pii/S2667305322000072/pdf |
| OpenAlex ID | https://openalex.org/W4211169133 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Mohammed Abdullahi](https://scholariq.org/researchers/mohammed-abdullahi/)

## Paper journal

- [Intelligent Systems with Applications](https://scholariq.org/journals/intelligent-systems-with-applications/)

## Paper primary topic

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

## Paper topics

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Digital Imaging for Blood Diseases](https://scholariq.org/topics/digital-imaging-for-blood-diseases/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

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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.