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Comparative Evaluation of Advanced Deep Learning, Image-to-Text Models, and Radiomics for Predicting Tumor Budding and Tumor-Stroma Ratio from Breast Ultrasound in Invasive Ductal Carcinoma.

1/5 보강
Academic radiology 📖 저널 OA 6.4% 2023: 1/1 OA 2024: 1/8 OA 2025: 4/67 OA 2026: 4/79 OA 2023~2026 2026 Vol.33(1) p. 61-76
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
153 patients diagnosed with histopathologically invasive ductal carcinoma.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSION] The findings obtained indicate that radiomics-based ML models show promise in non-invasive TB and TSR prediction using ultrasound images in breast cancer. The clinical integration of these approaches could significantly contribute to the development of personalized treatment strategies for invasive ductal carcinoma and enhance patient management.

Kaba E, Tören M, Asan B, Çubukçu Y, Öztürk G, Okcu O


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