Background Artificial intelligence (AI) is increasingly being used in medical imaging
analysis. We aimed to evaluate the diagnostic accuracy of AI models used for detection of …

Background Machine learning (ML) has been introduced in various fields of healthcare. In
colorectal surgery, the role of ML has yet to be reported. In this systematic review, an …

Objectives Radiomics image data analysis offers promising approaches in research but has
not been implemented in clinical practice yet, partly due to the instability of many …

Feature stability and standardization remain challenges that impede the clinical
implementation of radiomics. This study investigates the potential of spectral reconstructions …

Purpose Although radiation therapy is one of the most significant treatment modalities for
localized prostate cancer, the prognostic factors for biochemical recurrence (BCR) regarding …

Rationale and Objectives To develop a magnetic resonance imaging (MRI)-based radiomics
model for preoperative prediction of lateral pelvic lymph node (LPLN) metastasis (LPLNM) in …

Objectives A radiomics-based explainable eXtreme Gradient Boosting (XGBoost) model was
developed to predict central cervical lymph node metastasis (CCLNM) in patients with …

Objective: Lateral pelvic lymph node (LPLN) metastases are an important cause of
preventable local failure in rectal cancer. The aim of this study was to evaluate clinical and …

Simple Summary Colorectal carcinoma is characterized by intratumoral heterogeneity that
can be assessed by radiogenomics. Radiomics, high-throughput quantitative data extracted …

Half of the local regional recurrences from rectal cancer are nowadays located in the lateral
compartments, most likely due to lateral lymph node (LLN) metastases. There is evidence …