Modern medicine is reliant on various medical imaging technologies for non-invasively
observing patients' anatomy. However, the interpretation of medical images can be highly …

Due to its widespread availability, low cost, feasibility at the patient's bedside and
accessibility even in low-resource settings, chest X-ray is one of the most requested …

Background and purpose To investigate the radiomic feature (RF) repeatability via
perturbation and its impact on cross-institutional prognostic model generalizability in …

Purpose To evaluate robustness of a radiomics-based support vector machine (SVM) model
for detection of visually occult PDA on pre-diagnostic CTs by simulating common variations …

Simple Summary Hepatocellular carcinoma (HCC) is one of the most prevalent and
devastating malignancies worldwide. An ongoing phase-II clinical trial assesses the efficacy …

Background The immunohistochemical test (IHC) of HER2 and HR can provide prognostic
information and treatment guidance for invasive breast cancer patients. We aimed to …

Radiomics, which integrates the comprehensive characterization of imaging phenotypes
with machine learning algorithms, is increasingly recognized for its potential in the diagnosis …

Background: Acute oral mucositis is the most common side effect for nasopharyngeal
carcinoma patients receiving radiotherapy. Improper or delayed intervention to severe AOM …

In recent years, the application of machine learning (ML) techniques in research on the
prediction of post-traumatic stress disorder (PTSD) has increased. However, concerns …

Omics fusion has emerged as a crucial preprocessing approach in medical image
processing, significantly assisting several studies. One of the challenges encountered in …