Computer-extracted tumour characteristics have been incorporated into medical imaging
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …

Cervical cancer remains a leading cause of cancer death in women, seriously threatening
their physical and mental health. It is an easily preventable cancer with early screening and …

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 …

Purpose To introduce a novel deep learning (DL) T2-weighted TSE imaging (T2 DL)
sequence in prostate MRI and investigate its impact on examination time, image quality …

Background The tumor immune microenvironment (TIME) phenotypes have been reported
to mainly impact the efficacy of immunotherapy. Given the increasing use of immunotherapy …

The volume and complexity of scientific and clinical data in oncology have grown markedly
over recent years, including but not limited to the realms of electronic health data …

This study develops, validates, and deploys deep learning for automated total kidney
volume (TKV) measurement (a marker of disease severity) on T2-weighted MRI studies of …

Early diagnosis of abnormal cervical cells enhances the chance of prompt treatment for
cervical cancer (CrC). Artificial intelligence (AI)‐assisted decision support systems for …

The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit
detail from large datasets have attracted substantial research attention in the field of medical …

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 …