A radiomics feature-based machine learning models to detect brainstem infarction (RMEBI) may enable early diagnosis in non-contrast enhanced CT.

MLA

Zhang, Haiyan, et al. “A Radiomics Feature-Based Machine Learning Models to Detect Brainstem Infarction (RMEBI) May Enable Early Diagnosis in Non-Contrast Enhanced CT.” European Radiology, vol. 33, no. 2, Feb. 2023, pp. 1004–14. EBSCOhost, https://doi.org/10.1007/s00330-022-09130-6.

APA

Zhang, H., Chen, H., Zhang, C., Cao, A., Lu, Q., Wu, H., Zhang, J., & Geng, D. (2023). A radiomics feature-based machine learning models to detect brainstem infarction (RMEBI) may enable early diagnosis in non-contrast enhanced CT. European Radiology, 33(2), 1004–1014. https://doi.org/10.1007/s00330-022-09130-6

Chicago

Zhang, Haiyan, Hongyi Chen, Chao Zhang, Aihong Cao, Qingqing Lu, Hao Wu, Jun Zhang, and Daoying Geng. 2023. “A Radiomics Feature-Based Machine Learning Models to Detect Brainstem Infarction (RMEBI) May Enable Early Diagnosis in Non-Contrast Enhanced CT.” European Radiology 33 (2): 1004–14. doi:10.1007/s00330-022-09130-6.