# A comparative assessment of machine learning algorithms with the Least Absolute Shrinkage and Selection Operator for breast cancer detection and prediction

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-comparative-assessment-of-machine-learning-algorithms-with-the-least-absolute/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Md. Mehedi Hassan,Md. Mehedi Hassan,Md. Mahedi Hassan,Md. Mahedi Hassan,Farhana Yasmin,Md. Asif Rakib Khan,Sadika Zaman,Galibuzzaman,Khan Kamrul Islam,Anupam Kumar Bairagi |
| Citations | 83 |
| DOI | 10.1016/j.dajour.2023.100245 |
| Fields | Biochemistry, Genetics and Molecular Biology,Computer Science,Health Professions |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1016/j.dajour.2023.100245 |
| OpenAlex ID | https://openalex.org/W4372193958 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Anupam Kumar Bairagi](https://scholariq.org/researchers/anupam-kumar-bairagi/)

## 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/)
- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-in-healthcare/)
- [Gene expression and cancer classification](https://scholariq.org/topics/gene-expression-and-cancer-classification/)

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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.