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F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients.

2/5 보강
Abdominal radiology (New York) 📖 저널 OA 20.5% 2021: 0/1 OA 2022: 0/1 OA 2023: 1/2 OA 2024: 3/15 OA 2025: 16/79 OA 2026: 27/129 OA 2021~2026 2026 Vol.51(5) p. 2304-2316 OA Medical Imaging Techniques and Appli
TL;DR The Fusion model outperformed the Radiomics and Clinical models in predicting lymphovascular invasion in colorectal cancer patients and showed good clinical utility and calibration, proving its potential as a precision medical support tool for CRC patients.
Retraction 확인
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PubMed DOI PMC OpenAlex Semantic 마지막 보강 2026-04-29

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
추출되지 않음
I · Intervention 중재 / 시술
preoperative F-FDG PET/computed tomography were enrolled and assigned to the training cohort or the internal test cohort
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Moreover, it showed good clinical utility and calibration. [CONCLUSION] The 2.5D ensemble DL model based on F-FDG PET images performed well for the prediction of LVI in CRC, proving its potential as a precision medical support tool for CRC patients.
OpenAlex 토픽 · Medical Imaging Techniques and Applications Radiomics and Machine Learning in Medical Imaging Lung Cancer Diagnosis and Treatment

Zhao H, Lyu Z, Su Y, Zhang H, Zhang Z, Xu P

📖 무료 전문 🟢 PMC 전문 PMC13061801 🔓 OA PDF oa
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