# Prediction and Detection of Cervical Malignancy Using Machine Learning Models

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/prediction-and-detection-of-cervical-malignancy-using-machine-learning-models/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Seeta Devi,Sachin Gaikwad,R Harikrishnan |
| Citations | 42 |
| DOI | 10.31557/apjcp.2023.24.4.1419 |
| Fields | Computer Science,Health Professions,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://journal.waocp.org/article_90591_dc880b2a90dd25a00e624cb1249fade5.pdf |
| OpenAlex ID | https://openalex.org/W4367307511 |
| PMID | 37116167 |
| Type | article |
| Year | 2023 |

## Paper authors

- [R Harikrishnan](https://scholariq.org/researchers/r-harikrishnan/)

## Paper journal

- [Asian Pacific Journal of Cancer Prevention](https://scholariq.org/journals/asian-pacific-journal-of-cancer-prevention/)

## 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/)
- [Cervical Cancer and HPV Research](https://scholariq.org/topics/cervical-cancer-and-hpv-research/)
- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-in-healthcare/)

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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.