# A Systematic Study of Artificial Intelligence-Based Methods for Detecting Brain Tumors

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-systematic-study-of-artificial-intelligence-based-methods-for-detecting-brain/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sanjeet Kumar,Urmila Pilania,Neha Nandal |
| Citations | 12 |
| DOI | 10.15622/ia.22.3.3 |
| Fields | Computer Science,Medicine,Neuroscience |
| Open Access | true |
| OA Status | diamond |
| OA URL | http://ia.spcras.ru/index.php/sp/article/download/15692/15224 |
| OpenAlex ID | https://openalex.org/W4377861344 |
| Type | article |
| Year | 2023 |

## Paper authors

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

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

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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.