Cancer is a complicated global health concern with a significant fatality rate. Breast cancer is
among the leading causes of mortality each year. Advancements in prognoses have been …

Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented
in all fields, including medicine. As a relatively new domain, all efforts are directed towards …

In the fundus image segmentation process, more than one professional rater is usually
required to mark the organ in the image to reduce the error rate of diagnosis. However, it is …

The paper explored the problem of automatic diagnosis based on immunohistochemical
image analysis. The issue of automated diagnosis is a preliminary and advisory statement …

The success of immuno-oncology treatments promises long-term cancer remission for an
increasing number of patients. The response to checkpoint inhibitor drugs has shown a …

The field of immunology is fundamental to our understanding of the intricate dynamics of the
tumor microenvironment. In particular, tumor-infiltrating lymphocyte (TIL) assessment …

Simple Summary This study proposes an innovative approach to automatically identify
invasive carcinoma regions in breast cancer immunohistochemistry whole-slide images …

Recent studies have demonstrated the effectiveness of the combination of machine learning
and logical reasoning, including data-driven logical reasoning, knowledge driven machine …

An automated nuclei segmentation is the key technique for understanding and analyzing
cellular properties, which are helpful for disease diagnosis and support computer-aided …

Manually annotating nuclei from the gigapixel Hematoxylin and Eosin (H&E)-stained Whole
Slide Images (WSIs) is a laborious and costly task, meaning automated algorithms for cell …