Assessment of the quality and current performance of computed tomography (CT) radiomics-
based models in predicting epidermal growth factor receptor (EGFR) mutation status in …

Rationale and Objectives Timely identifying T790M mutation for non-small cell lung cancer
(NSCLC) patients with brain metastases (BM) is essential to adjust targeted treatment …

Actionable mutations refer to DNA alterations that, if detected, would be expected to affect
patients' response to treatments [1]. Among these actionable mutations, the most clinically …

The objective of this study is to develop a machine-learning model that can accurately
distinguish between different histologic types of brain lesions in patients with non-small cell …

Purpose This study aimed to explore the efficacy of the computed tomography (CT)
radiomics model for predicting the Ki-67 proliferation index (PI) of pure-solid non-small cell …

Background We aimed to predict human epidermal growth factor receptor 2 (HER2) 2+
status in patients with breast cancer by constructing and validating machine learning models …

To evaluate the efficacy of radiomics features extracted from preoperative high-resolution
computed tomography (HRCT) scans in distinguishing benign and malignant pulmonary …

Anatomical variations in shape and volume metrics make pancreas medical image
processing one of the most difficult subjects. Image processing in pancreas Computed …

It is important to note that the cure rates in cases of advanced stages of lung cancer are
remarkably low, which stresses out the importance for early detection as means to increase …

Purpose Extracting image features can predict the prognosis and treatment effect of non-
small cell lung cancer, which has been increasingly confirmed. However, the specific …