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1. Deep Learning Generates Synthetic Cancer Histology for Explainability and Education

2. Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology

4. Highly aneuploid non-small cell lung cancer shows enhanced responsiveness to concurrent radiation and immune checkpoint blockade

6. Factors associated with delays in care of suspicious lung nodules at an academic medical center.

7. Lymphatic coagulation and neutrophil extracellular traps in lung-draining lymph nodes of COVID-19 decedents

8. EPHA2 mutations with oncogenic characteristics in squamous cell lung cancer and malignant pleural mesothelioma.

9. Integrative Molecular Characterization of Malignant Pleural Mesothelioma

11. The concept of mesothelioma in situ, with consideration of its potential impact on cytology diagnosis

12. Contributors

14. Malignant peritoneal mesothelioma: prognostic significance of clinical and pathologic parameters and validation of a nuclear-grading system in a multi-institutional series of 225 cases

15. Differential responsiveness of MET inhibition in non-small-cell lung cancer with altered CBL.

16. Interstitial Pneumonia With Autoimmune Features: Value of Histopathology

17. CT Findings, Radiologic-Pathologic Correlation, and Imaging Predictors of Survival for Patients With Interstitial Pneumonia With Autoimmune Features.

20. Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes.

21. Telomere biology disorder prevalence and phenotypes in adults with familial hematologic and/or pulmonary presentations

22. Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center

27. Characterisation of patients with interstitial pneumonia with autoimmune features

33. Mesothelioma in situ of the peritoneum: report of three cases and review of the literature.

36. Germline Variants Incidentally Detected via Tumor-Only Genomic Profiling of Patients With Mesothelioma

37. Diffuse Alveolar Damage

39. Nuclear grade and necrosis predict prognosis in malignant epithelioid pleural mesothelioma: a multi-institutional study

40. Deep learning generates synthetic cancer histology for explainability and education

43. Updates on grading mesothelioma.

45. Surgical phenotype of patients with peritoneal mesothelioma and a germline mutation

46. Table S6 from Integrative Molecular Characterization of Malignant Pleural Mesothelioma

47. Data from Integrative Molecular Characterization of Malignant Pleural Mesothelioma

48. Supplementary Data from Integrative Molecular Characterization of Malignant Pleural Mesothelioma

50. Supplementary Table 2 from Paxillin Is a Target for Somatic Mutations in Lung Cancer: Implications for Cell Growth and Invasion

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