ISO-690 (author-date, English)

LI W, ZHOU Y, LUO Z, TAN M, YIN R und LI J, 2025. XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy. Frontiers in endocrinology. 29 Juli 2025. Vol. 16, , p. 1639639-1639639. DOI 10.3389/fendo.2025.1639639.

Elsevier - Harvard (with titles)

Li W, Zhou Y, Luo Z, Tan M, Yin R, Li J, 2025. XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy. Frontiers in endocrinology 16, 1639639-1639639. https://doi.org/10.3389/fendo.2025.1639639

American Psychological Association 7th edition

Li W, Zhou Y, Luo Z, Tan M, Yin R, & Li J. (2025). XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy. Frontiers in Endocrinology, 16, 1639639-1639639. https://doi.org/10.3389/fendo.2025.1639639

Springer - Basic (author-date)

Li W, Zhou Y, Luo Z, Tan M, Yin R, Li J (2025) XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy.. Frontiers in endocrinology 16:1639639-1639639. https://doi.org/10.3389/fendo.2025.1639639

Juristische Zitierweise (Stüber) (Deutsch)

Li W/ Zhou Y/ Luo Z/ Tan M/ Yin R/ Li J, XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy., Frontiers in endocrinology 2025, 1639639-1639639.

Bitte prüfen Sie die Zitate auf Korrektheit, bevor Sie diese in Ihre Arbeit einfügen.