# YOLOv5x-based Brain Tumor Detection for Healthcare Applications

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/yolov5x-based-brain-tumor-detection-for-healthcare-applications/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Manoj Kumar,Urmila Pilania,Stuti Thakur,Tanisha Bhayana |
| Citations | 18 |
| DOI | 10.1016/j.procs.2024.03.284 |
| Fields | Computer Science,Medicine,Neuroscience |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://doi.org/10.1016/j.procs.2024.03.284 |
| OpenAlex ID | https://openalex.org/W4394565354 |
| Type | conference-paper |
| Year | 2024 |

## Paper authors

- [Urmila Pilania](https://scholariq.org/researchers/urmila-pilania/)

## Paper journal

- [Procedia Computer Science](https://scholariq.org/journals/procedia-computer-science/)

## 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/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

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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.