Research graph
References from Structure-based analysis of immunohistochemical expression of P53 and BCL2 in breast cancer. Local targets link to admitted publications; unresolved targets remain external evidence.
Comparison of different scoring systems for immunohistochemical staining
10.1136/jcp.52.1.75 · 1999 · External reference
p53 protein expression patterns associated with TP53 mutations in breast carcinoma
10.1007/s10549-024-07357-z · 2024 · External reference
Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer
10.1038/labinvest.2017.131 · 2018 · External reference
Bcl-2 is a prognostic marker in breast cancer independently of the Nottingham Prognostic Index
10.1158/1078-0432.ccr-05-2719 · 2006 · External reference
Digital validation in breast cancer needle biopsies: comparison of histological grade and biomarker expression assessment using conventional light microscopy, whole slide imaging, and digital image analysis
10.3390/jpm14030312 · 2024 · External reference
BCL2 in breast cancer: a favourable prognostic marker across molecular subtypes and independent of adjuvant therapy received
10.1038/sj.bjc.6605921 · 2010 · External reference
A fully automated quantitative analysis method based on deep learning algorithms for immunohistochemical staining expression intensities
10.1016/j.intonc.2025.06.001 · 2025 · External reference
Multiscale vessel enhancement filtering
1998 · External reference
Histopathological image analysis: a review
10.1109/rbme.2009.2034865 · 2009 · External reference
Unresolved reference
2006 · External reference
Prognostic influences of BCL1 and BCL2 expression on disease-free survival in breast cancer
10.1038/s41598-021-90506-x · 2021 · External reference
Repurposing risperidone as an anti-angiogenic agent for triple-negative breast cancer: a computational to in ovo investigation
10.3389/fonc.2025.1645905 · 2025 · External reference
Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases
10.4103/2153-3539.186902 · 2016 · External reference
A Hessian-based deep learning preprocessing method for coronary angiography image analysis
10.3390/electronics13183676 · 2024 · External reference
SlideGraph+: Whole slide image level graphs to predict HER2 status in breast cancer
10.1016/j.media.2022.102486 · 2022 · External reference
Breast Cancer-Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies-An Updated Review
10.3390/cancers13174287 · 2021 · External reference
Image analysis and machine learning in digital pathology: challenges and opportunities
10.1016/j.media.2016.06.037 · 2016 · External reference
Application of immunohistochemistry in clinical practices as a standardized assay for breast cancer
10.1267/ahc.22-00050 · 2023 · External reference
The future of cancer diagnosis and treatment: unlocking the power of biomarkers and personalized molecular-targeted therapies
10.3390/jmp6030020 · 2025 · External reference
Histopathological images analysis and predictive modeling implemented in digital pathology-current affairs and perspectives
2023 · External reference
System for quantitative evaluation of DAB&H-stained breast cancer biopsy digital images (CHISEL)
10.1038/s41598-021-88611-y · 2021 · External reference
Quantification of immunohistochemistry—Issues concerning methods, utility and semiquantitative assessment II
10.1111/j.1365-2559.2006.02513.x · 2006 · External reference
Immunohistochemical detection of p53 and Bcl-2 in colorectal carcinoma: no evidence for prognostic significance
10.1038/bjc.1998.306 · 1998 · External reference
Expression of Bcl-2 in node-negative breast cancer is associated with various prognostic factors, but does not predict response to one course of perioperative chemotherapy
10.1038/bjc.1996.319 · 1996 · External reference
Confocal fluorescence microscopy for real-time breast cancer diagnosis: current advances and future perspectives
10.3389/fmede.2025.1607453 · 2025 · External reference
Significance of immunohistochemistry in breast cancer
10.5306/wjco.v5.i3.382 · 2014 · External reference
p53 protein expression patterns associated with TP53 mutations in breast carcinoma
10.1007/s10549-024-07357-z · ExternalCitation · doi-reference
A fully automated quantitative analysis method based on deep learning algorithms for immunohistochemical staining expression intensities
10.1016/j.intonc.2025.06.001 · ExternalCitation · doi-reference
Image analysis and machine learning in digital pathology: challenges and opportunities
10.1016/j.media.2016.06.037 · ExternalCitation · doi-reference
SlideGraph+: Whole slide image level graphs to predict HER2 status in breast cancer
10.1016/j.media.2022.102486 · ExternalCitation · doi-reference
Expression of Bcl-2 in node-negative breast cancer is associated with various prognostic factors, but does not predict response to one course of perioperative chemotherapy
10.1038/bjc.1996.319 · ExternalCitation · doi-reference
Immunohistochemical detection of p53 and Bcl-2 in colorectal carcinoma: no evidence for prognostic significance
10.1038/bjc.1998.306 · ExternalCitation · doi-reference
Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer
10.1038/labinvest.2017.131 · ExternalCitation · doi-reference
System for quantitative evaluation of DAB&H-stained breast cancer biopsy digital images (CHISEL)
10.1038/s41598-021-88611-y · ExternalCitation · doi-reference
Prognostic influences of BCL1 and BCL2 expression on disease-free survival in breast cancer
10.1038/s41598-021-90506-x · ExternalCitation · doi-reference
BCL2 in breast cancer: a favourable prognostic marker across molecular subtypes and independent of adjuvant therapy received
10.1038/sj.bjc.6605921 · ExternalCitation · doi-reference
Histopathological image analysis: a review
10.1109/rbme.2009.2034865 · ExternalCitation · doi-reference
Quantification of immunohistochemistry—Issues concerning methods, utility and semiquantitative assessment II
10.1111/j.1365-2559.2006.02513.x · ExternalCitation · doi-reference
Comparison of different scoring systems for immunohistochemical staining
10.1136/jcp.52.1.75 · ExternalCitation · doi-reference
Bcl-2 is a prognostic marker in breast cancer independently of the Nottingham Prognostic Index
10.1158/1078-0432.ccr-05-2719 · ExternalCitation · doi-reference
Application of immunohistochemistry in clinical practices as a standardized assay for breast cancer
10.1267/ahc.22-00050 · ExternalCitation · doi-reference
Confocal fluorescence microscopy for real-time breast cancer diagnosis: current advances and future perspectives
10.3389/fmede.2025.1607453 · ExternalCitation · doi-reference
Repurposing risperidone as an anti-angiogenic agent for triple-negative breast cancer: a computational to in ovo investigation
10.3389/fonc.2025.1645905 · ExternalCitation · doi-reference
Breast Cancer-Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies-An Updated Review
10.3390/cancers13174287 · ExternalCitation · doi-reference
A Hessian-based deep learning preprocessing method for coronary angiography image analysis
10.3390/electronics13183676 · ExternalCitation · doi-reference
The future of cancer diagnosis and treatment: unlocking the power of biomarkers and personalized molecular-targeted therapies
10.3390/jmp6030020 · ExternalCitation · doi-reference
Digital validation in breast cancer needle biopsies: comparison of histological grade and biomarker expression assessment using conventional light microscopy, whole slide imaging, and digital image analysis
10.3390/jpm14030312 · ExternalCitation · doi-reference
Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases
10.4103/2153-3539.186902 · ExternalCitation · doi-reference
Significance of immunohistochemistry in breast cancer
10.5306/wjco.v5.i3.382 · ExternalCitation · doi-reference
