| scholarly article | Q13442814 |
| P356 | DOI | 10.1038/MODPATHOL.2016.34 |
| P698 | PubMed publication ID | 26916072 |
| P50 | author | Johan Hartman | Q53409616 |
| Gustav Stålhammar | Q61104967 | ||
| P2093 | author name string | Mattias Rantalainen | |
| Lars Pedersen | |||
| Jonas Bergh | |||
| Nicholas P Tobin | |||
| Gustaf Rosin | |||
| Lorand Kis | |||
| Michael Lippert | |||
| Michael Grunkin | |||
| Ida Mølholm | |||
| Nelson Fuentes Martinez | |||
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| P433 | issue | 4 | |
| P921 | main subject | image analysis | Q860755 |
| biomarker | Q864574 | ||
| P304 | page(s) | 318-329 | |
| P577 | publication date | 2016-02-26 | |
| P1433 | published in | Modern Pathology | Q15724578 |
| P1476 | title | Digital image analysis outperforms manual biomarker assessment in breast cancer | |
| P478 | volume | 29 |
| Q47588672 | An inter-observer Ki67 reproducibility study applying two different assessment methods: on behalf of the Danish Scientific Committee of Pathology, Danish breast cancer cooperative group (DBCG). |
| Q40498847 | An update on the validation of whole slide imaging systems following FDA approval of a system for a routine pathology diagnostic service in the United States |
| Q40174538 | Automated histological classification of whole-slide images of gastric biopsy specimens |
| Q90505502 | Automated thresholding algorithms outperform manual thresholding in macular optical coherence tomography angiography image analysis |
| Q45945233 | Automatic cellularity assessment from post-treated breast surgical specimens. |
| Q89530705 | Cell engraftment, vascularization, and inflammation after treatment of equine distal limb wounds with endothelial colony forming cells encapsulated within hydrogel microspheres |
| Q90116551 | Commentary: Guideline for Performing Human Epidermal Growth Factor Receptor 2 Immunohistochemistry Quantitative Image Analysis well |
| Q37601727 | Construction and analysis of tissue microarrays in the era of digital pathology: a pilot study targeting CDX1 and CDX2 in a colon cancer cohort of 612 patients. |
| Q47321577 | Critical research gaps and recommendations to inform research prioritisation for more effective prevention and improved outcomes in colorectal cancer. |
| Q100454958 | Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region |
| Q64066522 | Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis |
| Q45943609 | Digital image analysis in breast pathology-from image processing techniques to artificial intelligence. |
| Q48212372 | Digital image analysis of Ki67 proliferation index in breast cancer using virtual dual staining on whole tissue sections: clinical validation and inter-platform agreement |
| Q90884771 | Digital image analysis of multiplex fluorescence IHC in colorectal cancer recognizes the prognostic value of CDX2 and its negative correlation with SOX2 |
| Q58609581 | Digital image analysis supports a nuclear-to-cytoplasmic ratio cutoff value below 0.7 for positive for high-grade urothelial carcinoma and suspicious for high-grade urothelial carcinoma in urine cytology specimens |
| Q98945179 | High throughput assessment of biomarkers in tissue microarrays using artificial intelligence: PTEN loss as a proof-of-principle in multi-center prostate cancer cohorts |
| Q38980634 | Image-based surrogate biomarkers for molecular subtypes of colorectal cancer |
| Q38823649 | Immune infiltrates in the breast cancer microenvironment: detection, characterization and clinical implication |
| Q41666190 | Impact of Altering Various Image Parameters on Human Epidermal Growth Factor Receptor 2 Image Analysis Data Quality |
| Q96954585 | Independent Prognostic Value of Intratumoral Heterogeneity and Immune Response Features by Automated Digital Immunohistochemistry Analysis in Early Hormone Receptor-Positive Breast Carcinoma |
| Q47291975 | Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer |
| Q47140684 | Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling. |
| Q64115873 | Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association |
| Q89657645 | Introduction to digital pathology and computer-aided pathology |
| Q58698990 | Ki 67 assessment in breast cancer in an Egyptian population: a comparative study between manual assessment on optical microscopy and digital quantitative assessment |
| Q94655415 | Ki-67 proliferation index in neuroendocrine tumors: Can augmented reality microscopy with image analysis improve scoring? |
| Q91289324 | Ki67 reproducibility using digital image analysis: an inter-platform and inter-operator study |
| Q50045468 | Molecular Subtypes and Local-Regional Control of Breast Cancer. |
| Q47104255 | PRL‑3 increases the aggressive phenotype of prostate cancer cells in vitro and its expression correlates with high-grade prostate tumors in patients |
| Q37737882 | Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer |
| Q37453940 | Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers |
| Q38728048 | The role of informatics in patient-centered care and personalized medicine |
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