BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is difficult to detect early and highly aggressive, often leading to poor patient prognosis. Existing serum biomarkers like CA19-9 are limited in early diagnosis, failing to meet clinical needs. Mac...
BACKGROUND: The cytological diagnostic process of EUS-FNA smears is time-consuming and manpower-intensive, and the conclusion could be subjective and controversial. Moreover, the relative lack of cytopathologists has limited the widespread implementa...
OBJECTIVES: The potential of medical imaging to non-invasively assess intratumoral heterogeneity (ITH) is increasingly being recognized. This study aimed to investigate the value of the ITH-based deep learning model for preoperative prediction of his...
OBJECTIVES: To extract intratumoral, peritumoral, and integrated intratumoral-peritumoral CT radiomic features, develop multi-source radiomic models using various machine learning algorithms to identify the optimal model, and integrate clinical facto...
BACKGROUND: Early and accurate identification of epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients with brain metastases is critical for guiding targeted therapy. This study aimed to develop a deep...
BACKGROUND AND OBJECTIVE: Spread through air spaces (STAS) is an important factor in determining the aggressiveness and recurrence risk of lung cancer, especially in early-stage adenocarcinoma. Preoperative identification of STAS is crucial for optim...
As reported by the International Agency for Research on Cancer (IARC), the global incidence of cancer reached nearly 20 million new cases in recent years, with cancer-related fatalities amounting to around 9.7 million. This underscores the profound i...
BACKGROUND: Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibil...
OBJECTIVE: We aimed to develop a preoperative clinical radiomics survival prediction model based on the radiomics features via deep learning to provide a reference basis for preoperative assessment and treatment decisions for patients with gallbladde...
BACKGROUND: Bladder cancer (BLCA) exists a profound molecular diversity, with basal and luminal subtypes having different prognostic and therapeutic outcomes. Traditional methods for molecular subtyping are often time-consuming and resource-intensive...