# Enhanced Deep Learning Models for Efficient Stroke Detection Using MRI Brain Imagery

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/enhanced-deep-learning-models-for-efficient-stroke-detection-using-mri-brain/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Anitha Patil,Suresh Kumar Govindaraj |
| Citations | 9 |
| DOI | 10.17762/ijritcc.v11i3.6335 |
| Fields | Computer Science,Neuroscience,Social Sciences |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://ijritcc.org/index.php/ijritcc/article/download/6335/5781 |
| OpenAlex ID | https://openalex.org/W4367182588 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Anitha Patil](https://scholariq.org/researchers/anitha-patil/)

## Paper journal

- [International Journal on Recent and Innovation Trends in Computing and Communication](https://scholariq.org/journals/international-journal-on-recent-and-innovation-trends-in-computing-and/)

## 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/)
- [Advanced Computing and Algorithms](https://scholariq.org/topics/advanced-computing-and-algorithms/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

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