APA (7th ed.) Citation

Hao, J., Liu, M., Zhou, Z., Zhao, C., Dai, L., & Ouyang, S. Predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients through logistic regression: A model incorporating clinical characteristics, computed tomography (CT) imaging features, and tumor marker levels. PeerJ Inc.

Chicago Style (17th ed.) Citation

Hao, Jimin, Man Liu, Zhigang Zhou, Chunling Zhao, Liping Dai, and Songyun Ouyang. Predicting Epidermal Growth Factor Receptor (EGFR) Mutation Status in Non-small Cell Lung Cancer (NSCLC) Patients Through Logistic Regression: A Model Incorporating Clinical Characteristics, Computed Tomography (CT) Imaging Features, and Tumor Marker Levels. PeerJ Inc.

MLA (9th ed.) Citation

Hao, Jimin, et al. Predicting Epidermal Growth Factor Receptor (EGFR) Mutation Status in Non-small Cell Lung Cancer (NSCLC) Patients Through Logistic Regression: A Model Incorporating Clinical Characteristics, Computed Tomography (CT) Imaging Features, and Tumor Marker Levels. PeerJ Inc.