# A Combined Deep CNN: LSTM with a Random Forest Approach for Breast Cancer Diagnosis

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-combined-deep-cnn-lstm-with-a-random-forest-approach-for-breast-cancer/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Almas Begum,V. Dhilip Kumar,Junaid Asghar,D Hemalatha,G. Arulkumaran |
| Citations | 64 |
| DOI | 10.1155/2022/9299621 |
| Fields | Computer Science,Neuroscience |
| Open Access | true |
| OA Status | gold |
| OA URL | https://downloads.hindawi.com/journals/complexity/2022/9299621.pdf |
| OpenAlex ID | https://openalex.org/W4295120702 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Almas Begum](https://scholariq.org/researchers/almas-begum/)
- [D Hemalatha](https://scholariq.org/researchers/d-hemalatha/)

## Paper primary topic

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)

## Paper topics

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)
- [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/)

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