Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative
information from digital histopathology images. AI is expected to reduce workload for human …

Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …

Manual delineation of tumours in breast histopathology images is generally time-consuming
and laborious. Computer-aided detection systems can assist pathologists by detecting …

Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

Psoriasis is a chronic inflammatory skin disorder mediated by the immune response that
affects a large number of people. According to latest worldwide statistics, 125 million …

Abstract In the Futures Studies context, the Delphi-based scenario (DBS) is a valuable
method for setting future-oriented strategies and actions by gathering expert opinions in …

The non-parallel disease progression and curative effect are the difficulties of clinical
diagnosis and treatment decisions. Experts (doctors) constantly summarize these non …

Advancements in digital pathology and computing resources have made a significant impact
in the field of computational pathology for breast cancer diagnosis and treatment. However …

There are many different types of nuclei in a tumor tissue. We can identify the specific nuclei
and their distribution in the tissue to reflect the current cancer state of histopathological …

现有模型病理特征提取不充分以及开源数据集各类型数量不平衡等问题, 使得乳腺癌病理图像的
多分类研究仍具挑战性. 本研究提出了一种多尺度特征融合的改进残差网络乳腺癌病理图像多 …