DLAAD-deep learning algorithms assisted diagnosis of chest disease using radiographic medical images
Mosleh Hmoud Al-Adhaileh, Bayan M. Alsharbi, Theyazn H. H. Aldhyani, Sultan Ahmad, Mohammed Amin Almaiah, Zeyad A. T. Ahmed, Saad M. AbdelRahman, Elham Alzain, Shilpi Singh · 2025
Read DLAAD-deep learning algorithms assisted diagnosis of chest disease using radiographic medical images by Mosleh Hmoud Al-Adhaileh, Bayan M. Alsharbi, Theyazn H. H. Aldhyani, Sultan Ahmad, Mohammed Amin Almaiah, Zeyad A. T. Ahmed, Saad M. AbdelRahman, Elham Alzain, Shilpi Singh (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11926135.txt.
Description
Mosleh Hmoud Al-Adhaileh leads a team of nine authors in 2025 in building a deep learning aid for diagnosing chest disease from X-ray images. Pneumonia from viral infection is hard to spot on a chest film because it resembles other lung conditions, and current reading methods have limited accuracy.
Their system, DLAAD, starts from a proven mobile-sized image network and adapts it by transfer learning to chest radiographs. The aim is a tool light enough for ordinary medical devices yet sharp enough to help doctors separate pneumonia from look-alike diseases. The study reports the model's design and its diagnostic performance.
Catalog record
| CREATOR | Mosleh Hmoud Al-Adhaileh, Bayan M. Alsharbi, Theyazn H. H. Aldhyani, Sultan Ahmad, Mohammed Amin Almaiah, Zeyad A. T. Ahmed, Saad M. AbdelRahman, Elham Alzain, Shilpi Singh |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |