# CXR-MultiTaskNet a unified deep learning framework for joint disease localization and classification in chest radiographs

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/cxr-multitasknet-a-unified-deep-learning-framework-for-joint-disease/

## Facts

| Field | Value |
| --- | --- |
| Author Names | K. Hemant Kumar Reddy,Anitha Patil |
| Citations | 10 |
| DOI | 10.1038/s41598-025-16669-z |
| Fields | Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.nature.com/articles/s41598-025-16669-z.pdf |
| OpenAlex ID | https://openalex.org/W4413862735 |
| PMID | 40887506 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Anitha Patil](https://scholariq.org/researchers/anitha-patil/)

## Paper journal

- [Scientific Reports](https://scholariq.org/journals/scientific-reports/)

## 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/)
- [Lung Cancer Diagnosis and Treatment](https://scholariq.org/topics/lung-cancer-diagnosis-and-treatment/)

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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.