Simple Summary Lung cancer is one of the most common and deadly malignancies
worldwide. Microscopic examination of histological and cytological lung specimens can be a …

Training machine learning models for artificial intelligence (AI) applications in pathology
often requires extensive annotation by human experts, but there is little guidance on the …

Background and objectives The detection of tumor-infiltrating lymphocytes (TILs) could aid in
the development of objective measures of the infiltration grade and can support decision …

This manuscript provides a comprehensive overview of the application of artificial
intelligence (AI) in lung pathology, particularly in the diagnosis of lung cancer. It discusses …

Active Learning (AL) has the potential to solve a major problem of digital pathology: the
efficient acquisition of labeled data for machine learning algorithms. However, existing AL …

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with
epithelial ovarian cancer. However, the evaluation of TILs has not been applied to routine …

病理学是疾病诊断的金标准. 利用全切片扫描技术将病理切片转化为数字图像后,
人工智能特别是深度学习模型在病理学图像分析领域展现出了巨大潜力. 人工智能在肺癌全切片 …

Addressing the critical need for accurate prognostic biomarkers in cancer treatment,
quantifying tumor-infiltrating lymphocytes (TILs) in non-small cell lung cancer (NSCLC) …

(1) Purpose: Although assessment of tumor-infiltrating lymphocytes (TILs) has been
acknowledged to have important predictive prognostic value in muscle-invasive bladder …

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