An Integrated Multimodal-Based CAD System for Breast Cancer Diagnosis
Amal Sunba, Maha AlShammari, Afnan Almuhanna, Omer S. Alkhnbashi · 2024
Read An Integrated Multimodal-Based CAD System for Breast Cancer Diagnosis by Amal Sunba, Maha AlShammari, Afnan Almuhanna, Omer S. Alkhnbashi (2024) 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-11591763.txt.
Description
Amal Sunba and co-authors build a computer aid for breast cancer diagnosis in a 2024 paper. Such aids can ease doctor workload and sharpen accuracy. Past aids rarely mixed patient facts, such as age and breast density, with images from both breasts and two view angles. The team tests that full mix.
One approach voted among several classic models plus an image network and reached ninety percent accuracy. A second approach fused the fact-based and image features inside one deep model and reached ninety-three percent. Using both breasts beat using only the affected side. Readers get proof that context plus full imaging makes a stronger diagnostic aid.
Catalog record
| CREATOR | Amal Sunba, Maha AlShammari, Afnan Almuhanna, Omer S. Alkhnbashi |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 47 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |