The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …

Historically, medical imaging has been a qualitative or semi-quantitative modality. It is
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …

Background Breast cancer is highly heterogeneous, resulting in different treatment
responses to neoadjuvant chemotherapy (NAC) among patients. A noninvasive quantitative …

Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical
outcomes. However, the widespread methods for assessing ITH based on genomic …

Background Accurate identification of pCR to neoadjuvant chemotherapy (NAC) is essential
for determining appropriate surgery strategy and guiding resection extent in breast cancer …

Background: in current clinical practice, the standard evaluation for axillary lymph node
(ALN) status in breast cancer has a low efficiency and is based on an invasive procedure …

The advancement of artificial intelligence concurrent with the development of medical
imaging techniques provided a unique opportunity to turn medical imaging from mostly …

Background This study investigated the efficacy of radiomics to predict survival outcome for
locally advanced breast cancer (LABC) patients and the association of radiomics with tumor …

Objectives Breast cancer (BC) is the most common cancer in women worldwide, and
neoadjuvant chemotherapy (NAC) is considered the standard of treatment for most patients …

The achievement of the pathologic complete response (pCR) has been considered a metric
for the success of neoadjuvant chemotherapy (NAC) and a powerful surrogate indicator of …