Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
Cutting-edge technology and automation in the pathology laboratory
One of the goals of pathology is to standardize laboratory practices to increase the precision
and effectiveness of diagnostic testing, which will ultimately enhance patient care and …
and effectiveness of diagnostic testing, which will ultimately enhance patient care and …
A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer
Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …
A twin convolutional neural network with hybrid binary optimizer for multimodal breast cancer digital image classification
There is a wide application of deep learning technique to unimodal medical image analysis
with significant classification accuracy performance observed. However, real-world …
with significant classification accuracy performance observed. However, real-world …
Deep learning model improves tumor-infiltrating lymphocyte evaluation and therapeutic response prediction in breast cancer
Tumor-infiltrating lymphocytes (TILs) have been recognized as key players in the tumor
microenvironment of breast cancer, but substantial interobserver variability among …
microenvironment of breast cancer, but substantial interobserver variability among …
Convergence of evolving artificial intelligence and machine learning techniques in precision oncology
E Fountzilas, T Pearce, MA Baysal, A Chakraborty… - npj Digital …, 2025 - nature.com
The confluence of new technologies with artificial intelligence (AI) and machine learning
(ML) analytical techniques is rapidly advancing the field of precision oncology, promising to …
(ML) analytical techniques is rapidly advancing the field of precision oncology, promising to …
Future practices of breast pathology using digital and computational pathology
MG Hanna, E Brogi - Advances in Anatomic Pathology, 2023 - journals.lww.com
Pathology clinical practice has evolved by adopting technological advancements initially
regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and …
regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and …
Differentiation and risk stratification of basal cell carcinoma with deep learning on histopathologic images and measuring nuclei and tumor microenvironment features
X Lan, G Guo, X Wang, Q Yan, R Xue… - Skin Research and …, 2024 - Wiley Online Library
Background Nuclear pleomorphism and tumor microenvironment (TME) play a critical role in
cancer development and progression. Identifying most predictive nuclei and TME features of …
cancer development and progression. Identifying most predictive nuclei and TME features of …
Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and …
A Haghofer, E Parlak, A Bartel… - Veterinary …, 2024 - journals.sagepub.com
Variation in nuclear size and shape is an important criterion of malignancy for many tumor
types; however, categorical estimates by pathologists have poor reproducibility …
types; however, categorical estimates by pathologists have poor reproducibility …
[HTML][HTML] A population-level computational histologic signature for invasive breast cancer prognosis
Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists
grade the microscopic appearance of breast tissue using the Nottingham criteria, which is …
grade the microscopic appearance of breast tissue using the Nottingham criteria, which is …