ISO-690 (author-date, English)

ETEMADYRAD, N., GAO, Y., LI, Q., GUO, X., KRUEGER, F., LIN, Q., QIU, D. und ZHAO, L., 2024. Functional Connectivity Prediction With Deep Learning for Graph Transformation. IEEE Transactions on Neural Networks and Learning Systems, Neural Networks and Learning Systems, IEEE Transactions on, IEEE Trans. Neural Netw. Learning Syst. 1 April 2024. Vol. 35, no. 4, p. 4862-4875. DOI 10.1109/TNNLS.2022.3197337.

Elsevier - Harvard (with titles)

Etemadyrad, N., Gao, Y., Li, Q., Guo, X., Krueger, F., Lin, Q., Qiu, D., Zhao, L., 2024. Functional Connectivity Prediction With Deep Learning for Graph Transformation. IEEE Transactions on Neural Networks and Learning Systems, Neural Networks and Learning Systems, IEEE Transactions on, IEEE Trans. Neural Netw. Learning Syst. 35, 4862-4875. https://doi.org/10.1109/TNNLS.2022.3197337

American Psychological Association 7th edition

Etemadyrad, N., Gao, Y., Li, Q., Guo, X., Krueger, F., Lin, Q., Qiu, D., & Zhao, L. (2024). Functional Connectivity Prediction With Deep Learning for Graph Transformation. IEEE Transactions on Neural Networks and Learning Systems, Neural Networks and Learning Systems, IEEE Transactions On, IEEE Trans. Neural Netw. Learning Syst., 35(4), 4862-4875. https://doi.org/10.1109/TNNLS.2022.3197337

Springer - Basic (author-date)

Etemadyrad N, Gao Y, Li Q, Guo X, Krueger F, Lin Q, Qiu D, Zhao L (2024) Functional Connectivity Prediction With Deep Learning for Graph Transformation. IEEE Transactions on Neural Networks and Learning Systems, Neural Networks and Learning Systems, IEEE Transactions on, IEEE Trans. Neural Netw. Learning Syst. 35:4862-4875. https://doi.org/10.1109/TNNLS.2022.3197337

Juristische Zitierweise (Stüber) (Deutsch)

Etemadyrad, N./ Gao, Y./ Li, Q./ Guo, X./ Krueger, F./ Lin, Q./ Qiu, D./ Zhao, L., Functional Connectivity Prediction With Deep Learning for Graph Transformation, IEEE Transactions on Neural Networks and Learning Systems, Neural Networks and Learning Systems, IEEE Transactions on, IEEE Trans. Neural Netw. Learning Syst. 2024, 4862-4875.

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