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1. Validation Study for the N Descriptor of the Newly Proposed Ninth Edition of the TNM Staging System Proposed by the International Association for the Study of Lung Cancer.

2. The International Association for the Study of Lung Cancer (IASLC) Staging Project for Lung Cancer: Recommendation to Introduce Spread Through Air Spaces as a Histologic Descriptor in the Ninth Edition of the TNM Classification of Lung Cancer. Analysis of 4061 Pathologic Stage I NSCLC.

3. The International Association for the Study of Lung Cancer Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groups in the Forthcoming (Ninth) Edition of the TNM Classification for Lung Cancer.

4. The International Association for the Study of Lung Cancer Staging Project for Lung Cancer: Proposals for the Revision of the M Descriptors in the Forthcoming Ninth Edition of the TNM Classification for Lung Cancer.

5. The International Association for the Study of Lung Cancer Staging Project for Lung Cancer: Proposals for the Revision of the N Descriptors in the Forthcoming Ninth Edition of the TNM Classification for Lung Cancer.

6. Classification of subtypes including LCNEC in lung cancer biopsy slides using convolutional neural network from scratch.

7. High KIF11 expression is associated with poor outcome of NSCLC.

8. Subtyping non-small cell lung cancer by histology-guided spatial metabolomics.

9. Using a convolutional neural network for classification of squamous and non-squamous non-small cell lung cancer based on diagnostic histopathology HES images.

10. Prognostic value of different N1 lymph node zones in pN1M0 non-small cell lung cancer: a systematic review and meta-analysis.

11. Comparison of Two Proposed Changes to the Current Nodal Classification for Non--small Cell Lung Cancer Based on the Number and Ratio of Metastatic Lymph Nodes.

12. The impact of reclassifying cancers of unspecified histology on international differences in survival for small cell and non-small cell lung cancer (ICBP SurvMark-2 project).

13. A New Method for Syndrome Classification of Non-Small-Cell Lung Cancer Based on Data of Tongue and Pulse with Machine Learning.

14. The influence of the number of lymph nodes removed on the accuracy of a newly proposed N descriptor classification in patients with surgically-treated lung cancer.

15. Which N Descriptor Is More Predictive of Prognosis in Resected Non-small Cell Lung Cancer: The Number of Involved Nodal Stations or the Location-Based Pathological N Stage?

16. Association of Lung Adenocarcinoma Subtypes According to the IASLC/ATS/ERS Classification and Programmed Cell Death Ligand 1 (PD-L1) Expression in Tumor Cells.

17. Clinical and Prognostic Significance of CD117 in Non-Small Cell Lung Cancer: A Systemic Meta-Analysis.

18. Association of PARP1-specific polymorphisms and haplotypes with non-small cell lung cancer subtypes.

19. Revealing the subtyping of non-small cell lung cancer based on genomic evolutionary patterns by multi-region sequencing.

20. Durvalumab-associated vasculitis presenting as 'the blue toe syndrome'.

21. The Genomic Landscape of SMARCA4 Alterations and Associations with Outcomes in Patients with Lung Cancer.

22. Distinguishing Non-Small Cell Lung Cancer Subtypes in Fine Needle Aspiration Biopsies by Desorption Electrospray Ionization Mass Spectrometry Imaging.

23. Lung cancer cytology and small biopsy specimens: diagnosis, predictive biomarker testing, acquisition, triage, and management.

24. Molecular profiling of non-small cell lung cancer.

25. Classification Model to Estimate MIB-1 (Ki 67) Proliferation Index in NSCLC Patients Evaluated With 18 F-FDG-PET/CT.

26. Tumor-associated exosomal miRNA biomarkers to differentiate metastatic vs. nonmetastatic non-small cell lung cancer.

27. Performance of gene expression-based single sample predictors for assessment of clinicopathological subgroups and molecular subtypes in cancers: a case comparison study in non-small cell lung cancer.

28. Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers.

29. Intratumoral heterogeneity in programmed death-ligand 1 immunoreactivity is associated with variation in non-small cell lung carcinoma histotype.

30. Telomere-associated genes and telomeric lncRNAs are biomarker candidates in lung squamous cell carcinoma (LUSC).

31. Prognostic Classification of Multiple Primary Lung Cancers Based on a Ground-Glass Opacity Component.

32. Joint use of the radiomics method and frozen sections should be considered in the prediction of the final classification of peripheral lung adenocarcinoma manifesting as ground-glass nodules.

33. Computer-Aided Detection System for the Classification of Non-Small Cell Lung Lesions using SVM.

34. Classification and Imaging Findings of Lung Neoplasms.

35. [Protein expression of PD-L1 and clinico-pathological data in a cohort of 53 patients with resectable non small cell lung cancer (NSCLC). Concordance between clones (22C3 and 28-8) and observers. Correlation and prognostic value of clinico-pathological data].

36. Comparative study on the mutational profile of adenocarcinoma and squamous cell carcinoma predominant histologic subtypes in Chinese non-small cell lung cancer patients.

37. Clinical Features and Progression Pattern of Acquired T790M-positive Compared With T790M-negative EGFR Mutant Non-small-cell Lung Cancer: Catching Tumor and Clinical Heterogeneity Over Time Through Liquid Biopsy.

38. Defining oligometastatic non-small cell lung cancer: A simulated multidisciplinary expert opinion.

39. Incorporation of EGFR mutation status into M descriptor of new TNM classification influences survival curves in non-small cell lung cancer patients.

40. The utility of TTF-1, napsin A, CK5 and p63 staining in the sub-classification of non-small cell carcinoma of the lung.

41. Verification of T descriptor with consolidation size for sub-centimeter non-small cell lung cancer.

42. Actigraphy as an assessment of performance status in patients with advanced lung cancer.

43. Radiomics for Classification of Lung Cancer Histological Subtypes Based on Nonenhanced Computed Tomography.

44. The Landscape of Actionable Molecular Alterations in Immunomarker-Defined Large-Cell Carcinoma of the Lung.

45. Incorporation of a Molecular Prognostic Classifier Improves Conventional Non-Small Cell Lung Cancer Staging.

46. Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis.

47. [Diagnosis of lung biopsy employing the 2015 WHO criteria and detection of related oncogenic driver mutations].

48. Adequacy of EBUS-TBNA specimen for mutation analysis of lung cancer.

49. New revisions and current issues in the eighth edition of the TNM classification for non-small cell lung cancer.

50. Complementary value of electron microscopy and immunohistochemistry in the diagnosis of non-small cell lung cancer: A potential role for electron microscopy in the era of targeted therapy.

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