Background Bladder cancer (BCa) can be divided into muscle‐invasive BCa (MIBC) and
non− muscle‐invasive BCa (NMIBC). Whether the tumor infiltrates the detrusor muscle is a …

Rationale and Objectives To investigate the capability of delta-radiomics to predict
pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in …

Introduction As computational capabilities have advanced, radiologists and their
collaborators have looked for novel ways to analyze diagnostic images. This has resulted in …

Background Limited data was available for rapid and accurate detection of COVID-19 using
CT-based machine learning model. This study aimed to investigate the value of chest CT …

Locally advanced rectal cancer (LARC) response to neoadjuvant chemoradiotherapy
(nCRT) is very heterogeneous and up to 30% of patients are considered non-responders …

Purpose To develop and validate an Artificial Intelligence (AI) model based on texture
analysis of high-resolution T2 weighted MR images able 1) to predict pathologic Complete …

Introduction This work describes the development of a novel radiomics phantom designed
for magnetic resonance imaging (MRI) that can be used in a multicenter setting. The …

Purpose The purpose of this study was to develop and validate a deep learning (DL)‐based
radiomics model to predict the response to chemotherapy in colorectal liver metastases …

Purpose The objective of this study is finding an intensity based histogram (IBH) signature to
predict pathologic complete response (pCR) probability using only pre-treatment magnetic …

Few studies have reported the reproducibility and stability of ultrasound (US) images based
radiomics features obtained from automatic segmentation in oncology. The purpose of this …