Работы, цитирующие эту работу

Работ: 5

Работа: Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques

1. Multi-parametric assessment of cardiac magnetic resonance images to distinguish myocardial infarctions: A tensor-based radiomics feature

   Dehua Wang, Hayder Jasim Taher, Murtadha Al-Fatlawi +3

   СтатьяRadiomics and Machine Learning in Medical ImagingJournal of X-Ray Science and Technology2024Цитирований: 0

   ABIABI:AkademIndex/openalex/2024.article.002602

2. Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images

   Mohamed J. Saadh, Qusay Mohammed Hussain, Rafid Jihad Albadr +10

   СтатьяArtificial Intelligence in Healthcare and EducationBMC Musculoskeletal Disorders2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.001072

3. Reproducible meningioma grading across multi-center MRI protocols via hybrid radiomic and deep learning features

   Mohamed J. Saadh, Rafid Jihad Albadr, Dharmesh Sur +10

   СтатьяMeningioma and schwannoma managementNeuroradiology2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.001814

4. Radiomics meets transformers: A novel approach to tumor segmentation and classification in mammography for breast cancer

   Mohamed J. Saadh, Qusay Mohammed Hussain, Rafid Jihad Albadr +10

   СтатьяRadiomics and Machine Learning in Medical ImagingJournal of X-Ray Science and Technology2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002186

5. Integrating histopathology and immune marker analysis for machine learning-based colorectal cancer prognostics

   Mohamed J. Saadh, Tamara Nazar Saeed, Karar H. Alfarttoosi +10

   СтатьяAI in cancer detectionDiagnostic Pathology2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.article.004815