N. Lindeman

Computer Vision and Pattern Recognition · 2004–2019

A researcher in the Science corpus: 13 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 14 citations into it

Whom N. Lindeman trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. David G. Lowe (in Computer Vision and Pattern Recognition)

Papers from N. Lindeman's perspective

Ordered by how strongly the researchers N. Lindeman trusts endorse each paper. Same corpus, a different order for every researcher.

1. Representation Learning with Contrastive Predictive Coding
2. Image-to-Image Translation with Conditional Adversarial Networks
3. Multimodal Deep Learning
4. Erlotinib in lung cancer - molecular and clinical predictors of outcome. (New England Journal of Medicine)
5. Pathology and genetics of tumours of the lung , pleura, thymus and heart
6. Clinical Resistance to STI-571 Cancer Therapy Caused by BCR-ABL Gene Mutation or Amplification (Science)
7. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. (New England Journal of Medicine)
8. Semi-Supervised Classification with Graph Convolutional Networks (International Conference on Learning Representations)
9. Hepatocyte growth factor induces gefitinib resistance of lung adenocarcinoma with epidermal growth factor receptor-activating mutations. (Cancer Research)
10. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. (New England Journal of Medicine)

Their papers

• Characterizing the cancer genome in lung adenocarcinoma (2007) — 1,146 citations
• MET Amplification Leads to Gefitinib Resistance in Lung Cancer by Activating ERBB3 Signaling (2007) — 4,374 citations
• A novel ALK secondary mutation and EGFR signaling cause resistance to ALK kinase inhibitors (2011) — 620 citations
• Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis (2019) — 654 citations
• Circulating Tumor DNA Analysis in Patients With Cancer: American Society of Clinical Oncology and College of American Pathologists Joint Review. (2018) — 899 citations
• Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment With Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology (2018) — 922 citations
• Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. (2017) — 1,774 citations
• Molecular Testing Guideline for Selection of Lung Cancer Patients for EGFR and ALK Tyrosine Kinase Inhibitors (2013) — 1,308 citations
• Pre-existence and clonal selection of MET amplification in EGFR mutant NSCLC (2010) — 1,010 citations
• Unique Clinicopathologic Features Characterize ALK-rearranged Lung Adenocarcinoma in the Western Population (2009) — 680 citations
• EML4-ALK fusion gene and efficacy of an ALK kinase inhibitor in lung cancer (2008) — 1,002 citations
• LKB1 modulates lung cancer differentiation and metastasis (2007) — 1,083 citations
• EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy (2004) — 9,841 citations