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Author

Ansh Kapil

Observed names: A. Kapil, Kapil, Ansh
ORCID: 0000-0002-5079-6997
Observed ORCID: 0000-0002-5079-6997
OpenAlex ID: A5076486250
PL02.11 Normalized Membrane Ratio of TROP2 by Quantitative Continuous Scoring is Predictive of Clinical Outcomes in TROPION-Lung 01
2024 · M.C. Garassino, J. Sands, et al. · Journal of Thoracic Oncology · 95
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HER2 quantitative continuous scoring for accurate patient selection in HER2 negative trastuzumab deruxtecan treated breast cancer
2024 · Ansh Kapil, Andreas Spitzmüller, et al. · Scientific Reports · 51
Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images
2021 · Ansh Kapil, Armin Meier, et al. · IEEE Transactions on Medical Imaging · 37
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Abstract PD6-01: Novel approach to HER2 quantification: Digital pathology coupled with AI-based image and data analysis delivers objective and quantitative HER2 expression analysis for enrichment of responders to trastuzumab deruxtecan (T-DXd; DS-8201), specifically in HER2-low patients
2021 · Mark Gustavson, Susanne Haneder, et al. · Cancer Research · 30
DASGAN -- Joint Domain Adaptation and Segmentation for the Analysis of Epithelial Regions in Histopathology PD-L1 Images
2019 · Kapil, Ansh, Wiestler, Tobias, et al. · arXiv (Cornell University) · 19
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Domain Adaptation-based Augmentation for Weakly Supervised Nuclei Detection
2019 · Brieu, Nicolas, Meier, Armin, et al. · arXiv (Cornell University) · 16
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Shifting the paradigm in personalized cancer care through next‐generation therapeutics and computational pathology
2024 · Jorge S. Reis‐Filho, Maurizio Scaltriti, et al. · Molecular Oncology · 6
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Spatial heterogeneity of cancer associated protein expression in immunohistochemically stained images as an improved prognostic biomarker
2022 · Henrik Failmezger, Harald Hessel, et al. · Frontiers in Oncology · 6
Enhanced patient selection with quantitative continuous scoring of PD-L1 expression for IO treatment in metastatic NSCLC
2025 · J. Lesniak, M. Schick, et al. · npj Precision Oncology · 5
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Learning without prejudice: Avoiding bias in webly-supervised action recognition
2017 · Christian Rupprecht, Ansh Kapil, et al. · Computer Vision and Image Understanding · 5
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Abstract P6-04-03: Computational pathology based HER2 expression quantification in HER2-low breast cancer
2023 · Andreas Spitzmüller, Ansh Kapil, et al. · Cancer Research · 4
Abstract P2-09-03: Quantification of HER2 expression and spatial biology using computational pathology: A cross-assay validation study in breast cancer
2023 · Joshua Drago, Zonera Hassan, et al. · Cancer Research · 3
Computational pathology–based HER2 quantification to identify novel biomarkers in gastric cancer (GC).
2023 · Ansh Kapil, Henrik Failmezger, et al. · Journal of Clinical Oncology · 2
583 Quantitative computational assessment of PD-L1 enables robust patient selection for biomarker-informed anti-PD-L1 treatment of NSCLC patients
2022 · Jan Lesniak, Markus Schick, et al. · Journal for ImmunoTherapy of Cancer · 2
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Stain Isolation-based Guidance for Improved Stain Translation
2022 · Brieu, Nicolas, Segerer, Felix J., et al. · arXiv (Cornell University) · 2
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Abstract 468: Quantitative assessment of IHC using computational pathology allows superior patient selection for biomarker-informed patients
2022 · Hadassah Sade, Ansh Kapil, et al. · Cancer Research · 2
365 Computational pathology delivers objective and quantitative PD-L1 expression analysis for enrichment of responders to durvalumab in non-small cell lung cancer (NSCLC)
2021 · Guenter Schmidt, Ansh Kapil, et al. · Journal for ImmunoTherapy of Cancer · 2
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Breast cancer patient stratification using domain adaptation based lymphocyte detection in HER2 stained tissue sections
2021 · Ansh Kapil, Armin Meier, et al. · 2
Human Epidermal Growth Factor Receptor 2 Quantification Using Computational Pathology to Identify Novel Biomarkers for Trastuzumab Deruxtecan–Treated Human Epidermal Growth Factor Receptor 2–Positive Gastric Cancer
2026 · Ansh Kapil, Henrik Failmezger, et al. · JCO Precision Oncology · 1
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EP06.05-09 Computational Pathology-Based Assessment of cMET IHC Expression for Patient Selection in the Treatment of MET Overexpressing NSCLC
2023 · S. Christ, A. Kapil, et al. · Journal of Thoracic Oncology · 1
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339 Quantitative assessment of CAR-T cell therapy targets using computational pathology
2022 · Nathalie Harder, Markus Schick, et al. · Journal for ImmunoTherapy of Cancer · 1
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Novel Deep Learning Approach to Derive Cytokeratin Expression and Epithelium Segmentation from DAPI
2022 · Segerer, Felix Jakob, Nekolla, Katharina, et al. · arXiv (Cornell University) · 1
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Abstract PO4-26-01: Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine
2024 · Mark Gustavson, Markus Schick, et al. · Cancer Research
Leveraging weakly labeled datasets with target adaptive loss for cell segmentation in immunofluorescence images
2024 · Nicolas Brieu, Joshua Z. Drago, et al. · SPIE Medical Imaging: Digital and Computational Pathology
Abstract 5388: A unified computational pathology method to quantify HER2 expression from raw IHC and IF images in breast cancer
2023 · Nicolas Brieu, Joshua Z. Drago, et al. · Cancer Research
Works count: 28
Citation count: 293
H-index: 6
I10-index: 6
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