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Evaluation of MRI anatomy in machine learning predictive models to assess hydrogel spacer benefit for prostate cancer patients.

1/5 보강
Technical innovations & patient support in radiation oncology 2025 Vol.34() p. 100305
Retraction 확인
출처
PubMed DOI PMC

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
20 patients.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSION] Differences between pCT and dMRI anatomical ROI variables did not impact SML model performance in this study, demonstrating the feasibility of using dMRI images. Due to the limited sample size further training of the predictive models including dMRI anatomy is recommended.

Bush M, Jones S, Hargrave C

📖 무료 전문 🟢 PMC 전문 PMC11986981
PubMed ↗ DOI ↗ BibTeX ↓ RIS ↓

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