Работы, цитирующие эту работу

Работ: 4

Работа: Development and validation of a robust MRI-based nomogram incorporating radiomics and deep features for preoperative glioma grading: a multi-center study

1. Multi-objective deep learning for lung cancer detection in CT images: enhancements in tumor classification, localization, and diagnostic efficiency

   Abdulqader Faris Abdulqader, Shaymaa Mohammed Abdulameer, Ashok Kumar Bishoyi +10

   СтатьяLung Cancer Diagnosis and TreatmentDiscover Oncology2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.000234

2. 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

3. Optimizing meningioma grading with radiomics and deep features integration, attention mechanisms, and reproducibility analysis

   Rafid Jihad Albadr, Dharmesh Sur, Anupam Yadav +11

   СтатьяMeningioma and schwannoma managementEuropean journal of medical research2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002248

4. Transformer-based ultrasound radiomics for novel multi-task automated segmentation and classification of ovarian tumors

   Ahmed Faisal Mutee, Ali Fawzi Al-Hussainy, Nathier A. Ibrahim +10

   СтатьяOvarian cancer diagnosis and treatmentAbdominal Radiology2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.010370