Automated scoring methods for quantitative interpretation of Tumour infiltrating lymphocytes (TILs) in breast cancer: a systematic review
Tumour microenvironment (TME) of breast cancer mainly comprises malignant, stromal,
immune, and tumour infiltrating lymphocyte (TILs). Assessment of TILs is crucial for …
immune, and tumour infiltrating lymphocyte (TILs). Assessment of TILs is crucial for …
[HTML][HTML] Applications of artificial intelligence in digital pathology for gastric cancer
S Chen, P Ding, H Guo, L Meng, Q Zhao… - Frontiers in …, 2024 - pmc.ncbi.nlm.nih.gov
Gastric cancer is one of the most common cancers and is one of the leading causes of
cancer-related deaths in worldwide. Early diagnosis and treatment are essential for a …
cancer-related deaths in worldwide. Early diagnosis and treatment are essential for a …
[HTML][HTML] Quantifying the tumour vasculature environment from CD-31 immunohistochemistry images of breast cancer using deep learning based semantic …
Background Tumour vascular density assessed from CD-31 immunohistochemistry (IHC)
images has previously been shown to have prognostic value in breast cancer. Current …
images has previously been shown to have prognostic value in breast cancer. Current …
A more objective PD diagnostic model: integrating texture feature markers of cerebellar gray matter and white matter through machine learning
Y Chen, Y Qi, T Li, A Lin, Y Ni, R Pu… - Frontiers in Aging …, 2024 - frontiersin.org
Objective The purpose of this study is to explore whether machine learning can be used to
establish an effective model for the diagnosis of Parkinson's disease (PD) by using texture …
establish an effective model for the diagnosis of Parkinson's disease (PD) by using texture …
[HTML][HTML] Digital Whole Slide Image Analysis of Elevated Stromal Content and Extracellular Matrix Protein Expression Predicts Adverse Prognosis in Triple-Negative …
Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis
and limited treatment options. This study evaluates the prognostic value of stromal markers …
and limited treatment options. This study evaluates the prognostic value of stromal markers …
Machine Learning for Early Breast Cancer Detection
Globally, breast cancer (BC) remains a significant cause to female mortality. Early detection
of BC plays an important role in reducing premature deaths. Various imaging techniques …
of BC plays an important role in reducing premature deaths. Various imaging techniques …
[HTML][HTML] Research progress of artificial intelligence in evaluating the efficacy of neoadjuvant chemotherapy for breast cancer
Breast cancer is a major oncological challenge for females worldwide. The incorporation of
neoadjuvant chemotherapy into comprehensive management strategies for breast cancer …
neoadjuvant chemotherapy into comprehensive management strategies for breast cancer …
Machine learning and pathology: a historical perspective
S Malpani, R Paz, Y Mirzabeigi… - Artificial Intelligence in …, 2025 - Elsevier
Traditionally, diagnosis and classification in pathology have been based on the evaluation
of glass slides under the microscope. This conventional method has led to subjective …
of glass slides under the microscope. This conventional method has led to subjective …