Liang, X., Ke, X., Hu, W., Jiang, J., Li, S., Xue, C., . . . Zhou, J. (2025). Deep learning radiomic nomogram outperforms the clinical model in distinguishing intracranial solitary fibrous tumors from angiomatous meningiomas and can predict patient prognosis. European Radiology, 35(5), 2670-2681.
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Liang, Xiaohong, et al. "Deep Learning Radiomic Nomogram Outperforms the Clinical Model in Distinguishing Intracranial Solitary Fibrous Tumors from Angiomatous Meningiomas and Can Predict Patient Prognosis."
European Radiology 35, no. 5 (2025): 2670-2681.
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Cita MLA (9a ed.)
Liang, Xiaohong, et al. "Deep Learning Radiomic Nomogram Outperforms the Clinical Model in Distinguishing Intracranial Solitary Fibrous Tumors from Angiomatous Meningiomas and Can Predict Patient Prognosis."
European Radiology, vol. 35, no. 5, 2025, pp. 2670-2681.
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