# CardioXNet: A Novel Lightweight Deep Learning Framework for Cardiovascular Disease Classification Using Heart Sound Recordings

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/cardioxnet-a-novel-lightweight-deep-learning-framework-for-cardiovascular/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Samiul Based Shuvo,Shams Nafisa Ali,Soham Irtiza Swapnil,Mabrook Al‐Rakhami,Abdu Gumaei |
| Citations | 209 |
| DOI | 10.1109/access.2021.3063129 |
| Fields | Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/9312710/09366875.pdf |
| OpenAlex ID | https://openalex.org/W3135849576 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Mabrook Al‐Rakhami](https://scholariq.org/researchers/mabrook-al-rakhami/)
- [Abdu Gumaei](https://scholariq.org/researchers/abdu-gumaei/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## Paper primary topic

- [Phonocardiography and Auscultation Techniques](https://scholariq.org/topics/phonocardiography-and-auscultation-techniques/)

## Paper topics

- [Phonocardiography and Auscultation Techniques](https://scholariq.org/topics/phonocardiography-and-auscultation-techniques/)

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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.