# Explained Deep Learning Framework for COVID-19 Detection in Volumetric CT Images Aligned with the British Society of Thoracic Imaging Reporting Guidance: A Pilot Study

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/explained-deep-learning-framework-for-covid-19-detection-in-volumetric-ct-images/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Shereen Fouad,Muhammad Usman,Ra’eesa Kabir,Arvind Rajasekaran,John Morlese,Pankaj Nagori,Bahadar Bhatia |
| Citations | 6 |
| DOI | 10.1007/s10278-025-01444-3 |
| Fields | Medicine |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://link.springer.com/content/pdf/10.1007/s10278-025-01444-3.pdf |
| OpenAlex ID | https://openalex.org/W4407963328 |
| PMID | 40011345 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Bahadar Bhatia](https://scholariq.org/researchers/bahadar-bhatia/)

## Paper primary topic

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

## Paper topics

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)

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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.