Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative
metrics—the so-called radiomic features—within medical images. Radiomic features capture …

Radiomics research is rapidly growing in recent years, but more concerns on radiomics
reliability are also raised. This review attempts to update and overview the current status of …

Background Accurate prediction of treatment response to neoadjuvant chemotherapy
(NACT) in individual patients with locally advanced gastric cancer (LAGC) is essential for …

Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal
cancer. Adjuvant chemotherapy is usually used for distant control. However, not all patients …

Objectives Radiomic features derived from routine medical images show great potential for
personalized medicine in gastric cancer (GC). We aimed to evaluate the current status and …

Rationale: Given the rapid spread of COVID-19, an updated risk-stratify prognostic tool could
help clinicians identify the high-risk patients with worse prognoses. We aimed to develop a …

With the continuous development of medical image informatics technology, more and more
high-throughput quantitative data could be extracted from digital medical images, which has …

As a reliable preoperative predictor for microvascular invasion (MVI) and disease-free
survival (DFS) is lacking, we developed a radiomics nomogram of [18 F] FDG PET/CT to …

Current gastric cancer staging alone cannot predict prognosis and adjuvant chemotherapy
benefits in stage II and III gastric cancer. Tumor immune microenvironment biomarkers and …

Objectives A critical problem in radiomic studies is the high dimensionality of the datasets,
which stems from small sample sizes and many generic features extracted from the volume …