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2. Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

3. Increasing the usefulness of already existing annotations through WSI registration

4. Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study

7. A Career in Football: What is Behind an Outstanding Market Value?

8. Adherence to and optimization of guidelines for Risk of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study

9. Training pathologists to assess stromal tumour‐infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research

11. Unveiling the Power of Model-Agnostic Multiscale Analysis for Enhancing Artificial Intelligence Models in Breast Cancer Histopathology Images

12. Immune cell infiltrate in ductal carcinoma in situ and the risk of dying from breast cancer : case-control study

13. Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

14. Image-based multiplex immune profiling of cancer tissues:translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

15. Quantitative assessment of PD-L1 as an analyte in immunohistochemistry diagnostic assays using a standardized cell line tissue microarray

16. Image‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast Cancer

18. Interplay between copy number alterations and immune profiles in the early breast cancer Scandinavian Breast Group 2004-1 randomized phase II trial: results from a feasibility study

19. Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma

22. Automated scoring of tumour infiltrating lymphocytes informs risk of death from thin melanoma: a nested case-case study

23. Spatial analyses of immune cell infiltration in cancer: current methods and future directions. A report of the International Immuno‐Oncology Biomarker Working Group on Breast Cancer

24. Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

30. Abstract 5432: Validation of spatial gene expression patterns predicted by deep convolutional neural networks from breast cancer histopathology images

31. Supplementary Figure S2 from Survival Outcomes, Digital TILs, and On-treatment PET/CT During Neoadjuvant Therapy for HER2-positive Breast Cancer: Results from the Randomized PREDIX HER2 Trial

32. Supplementary Table S1 from Survival Outcomes, Digital TILs, and On-treatment PET/CT During Neoadjuvant Therapy for HER2-positive Breast Cancer: Results from the Randomized PREDIX HER2 Trial

33. Supplementary Data from Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death

37. Survival Outcomes, Digital TILs, and On-treatment PET/CT During Neoadjuvant Therapy for HER2-positive Breast Cancer : Results from the Randomized PREDIX HER2 Trial

38. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer:A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

39. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

40. Spatial analyses of immune cell infiltration in cancer: current methods and future directions. A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

41. Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer:a report of the international immuno-oncology biomarker working group

43. Survival Outcomes, Digital TILs, and On-treatment PET/CT During Neoadjuvant Therapy for HER2-positive Breast Cancer: Results from the Randomized PREDIX HER2 Trial

44. External Quality Assessment 2.0: The Importance of a Standardized Implementation of TILs for Daily and Trial Practices

45. Objective assessment of tumor infiltrating lymphocytes as a prognostic marker in melanoma using machine learning algorithms

48. Combined assessment of metabolic response and tumor infiltrating lymphocytes as a predictor of outcomes following neoadjuvant therapy for HER2-positive breast cancer: Results from the randomized PREDIX HER2 trial.

49. Real World Evaluation of the Prosigna/PAM50 Test in a Node-Negative Postmenopausal Swedish Population: A Multicenter Study

50. Real World Evaluation of the Prosigna/PAM50 Test in a Node-Negative Postmenopausal Swedish Population : A Multicenter Study

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