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A deep learning framework to stratify Nottingham histologic grade 2 breast tumors based on dynamic contrast-enhanced MRI.

4/5 보강

European radiology 📖 저널 OA 30.2% 2022~2026 2026 Vol.36(5) p. 3335-3345 cited 2 OA RCR 2.89 MRI in cancer diagnosis

TL;DR These findings demonstrate equivalent positive margin, re-excision, and recurrence rates between wire and RFID tag bracketed localization techniques with observed increased median specimen volume with tag localization.

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문

P · Population 대상 환자/모집단

환자: DRG2+ tumors had significantly worse RFS compared to DRG2- (adjusted hazard ratio = 2

I · Intervention 중재 / 시술

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C · Comparison 대조 / 비교

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O · Outcome 결과 / 결론

Patients with grade 3-like tumors had worse RFS: adjusted hazard ratio = 2.39 [95% CI: 1.29-4.45], p = 0.0059). Clinical relevance Risk stratification could inform treatment choice to minimize over- and under-treatment in patients with intermediate-risk breast cancer.

OpenAlex 토픽 · MRI in cancer diagnosis Breast Cancer Treatment Studies Radiomics and Machine Learning in Medical Imaging

Hadidchi R, Agrawal A, Liu MZ, Maldijan T, Zhu Y, Nguyen HQ

📖 무료 전문 🟢 PMC 전문 PMC13086883 🔓 OA PDF oa

PubMed ↗ DOI ↗ BibTeX ↓ RIS ↓

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