XceptRf-Net: A Novel Deep Learning and Machine Learning Approach for Pneumonia Diagnosis
The findings highlight the theoretical superiority of the integration of convolutional deep features with ensemble learning and the generation of probabilistic features for medical image analysis. The proposed method provides a stable and explainable framework for clinical decision support and has high potential for practical use in real-world systems for pediatric pneumonia screening and diagnosis.
Authors
- Kashif Munir (ORCID: https://orcid.org/0000-0001-5114-4213)
- Salil Bharany (ORCID: https://orcid.org/0000-0002-2282-0419)
- Syed Rizwan hassan
- Syed Ali Jafar Zaidi (ORCID: https://orcid.org/0000-0003-0470-0576)
- Muhammad Usama Tanveer
- Ateeq Ur Rehman
Institutions
- Chandigarh University (IN)
- Gachon University (KR)
- Applied Science Private University (JO)
- Khwaja Fareed University of Engineering and Information Technology (PK)
- Chitkara University (IN)
- Saveetha University (IN)
Publication Details
- Journal
- Current Medical Imaging Formerly Current Medical Imaging Reviews
- Published
- 2026-03-03
- DOI
- https://doi.org/10.2174/0115734056409581251202221437
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00