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Development of machine learning models to predict papillary carcinoma in thyroid nodules: The role of immunological, radiologic, cytologic and radiomic features.

1/5 보강

Auris, nasus, larynx 📖 저널 OA 12.7% 2021~2026 2024 Vol.51(6) p. 922-928

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문

P · Population 대상 환자/모집단

186 patients, 92 nodules (49.

I · Intervention 중재 / 시술

추출되지 않음

C · Comparison 대조 / 비교

추출되지 않음

O · Outcome 결과 / 결론

[CONCLUSION] ML algorithms demonstrated low accuracy when trained with clinical-immunological data. However, the inclusion of radiological data significantly improved the models' performance, while cytopathological and radiomics data did not further improve the accuracy.

Canali L, Gaino F, Costantino A, Guizzardi M, Carnicelli G, Gullà F

PubMed ↗ DOI ↗ BibTeX ↓ RIS ↓

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