Li, H., Chang, C., Zhou, B., Lan, Y., Zang, P., Chen, S., . . . Duan, Y. (2025). Radiomics machine learning based on asymmetrically prominent cortical and deep medullary veins combined with clinical features to predict prognosis in acute ischemic stroke. PeerJ, 13, e19469. https://doi.org/10.7717/peerj.19469
Chicago Style (17th ed.) CitationLi, Hongyi, Cancan Chang, Bo Zhou, Yu Lan, Peizhuo Zang, Shannan Chen, Shouliang Qi, Ronghui Ju, and Yang Duan. "Radiomics Machine Learning Based on Asymmetrically Prominent Cortical and Deep Medullary Veins Combined with Clinical Features to Predict Prognosis in Acute Ischemic Stroke." PeerJ 13 (2025): e19469. https://doi.org/10.7717/peerj.19469.
MLA (9th ed.) CitationLi, Hongyi, et al. "Radiomics Machine Learning Based on Asymmetrically Prominent Cortical and Deep Medullary Veins Combined with Clinical Features to Predict Prognosis in Acute Ischemic Stroke." PeerJ, vol. 13, 2025, p. e19469, https://doi.org/10.7717/peerj.19469.
