366 results on '"Almangush, Alhadi"'
Search Results
2. Psychological Factors Related to Treatment Outcomes in Head and Neck Cancer
3. Programmed death-ligand 1 and tumor-infiltrating lymphocytes (TILs) – low TIL density may predict poorer long-term prognosis in T1 laryngeal cancer
4. Accumulating evidence from meta-analyses of prognostic studies on oral cancer: towards biomarker-driven patient selection
5. The prognostic role of single cell invasion and nuclear diameter in early oral tongue squamous cell carcinoma
6. Correction to: Programmed death-ligand 1 and tumor-infiltrating lymphocytes (TILs) – low TIL density may predict poorer long-term prognosis in T1 laryngeal cancer
7. The risk of second primary cancer after nasopharyngeal cancer: a systematic review
8. Artificial Intelligence-Driven Radiomics in Head and Neck Cancer: Current Status and Future Prospects
9. Predictive value of tumor budding in head and neck squamous cell carcinoma: an update
10. Tumour budding in head and neck cancer: what have we learnt and the next steps towards clinical implementation
11. Application of artificial intelligence for overall survival risk stratification in oropharyngeal carcinoma: A validation of ProgTOOL
12. Tumor-stroma ratio is a promising prognostic classifier in oropharyngeal cancer
13. Prognostic Significance of Tumor-associated Stroma in Nasopharyngeal Carcinoma: A Multicenter Study
14. Can TILs supplement the TNM staging system (as TNM-Immune)?
15. An interpretable machine learning prognostic system for risk stratification in oropharyngeal cancer
16. Tumour-infiltrating lymphocytes in oropharyngeal cancer: a validation study according to the criteria of the International Immuno-Oncology Biomarker Working Group
17. Web‐based prognostic tools for oral tongue cancer: An analysis of online predictors.
18. Managing Cachexia in Head and Neck Cancer: a Systematic Scoping Review
19. Tertiary lymphoid structures associate with improved survival in early oral tongue cancer
20. Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future—A systematic review
21. Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with tongue cancer
22. Stromal categorization in early oral tongue cancer
23. High tumor mutation burden predicts favorable outcome among patients with aggressive histological subtypes of lung adenocarcinoma: A population-based single-institution study
24. Staging and grading of oral squamous cell carcinoma: An update
25. Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer
26. Artificial Intelligence-Driven radiomics in head and neck Cancer: Current status and future prospects
27. Characteristics of Laryngeal Osteosarcoma: A Critical Review
28. Clinical significance of tumor-stroma ratio in head and neck cancer: a systematic review and meta-analysis
29. Cellular dissociation: a missing item in the pathology report and histologic grading of oral tongue cancer?
30. Tumor-infiltrating lymphocytes associate with outcome in nonendemic nasopharyngeal carcinoma: a multicenter study
31. Machine learning application for prediction of locoregional recurrences in early oral tongue cancer: a Web-based prognostic tool
32. Assessment of tumor-infiltrating lymphocytes in head and neck cancer: Clinical scenarios
33. Prognostic Significance of Tumor-associated Stroma in Nasopharyngeal Carcinoma
34. Correction to: Programmed death-ligand 1 and tumor-infiltrating lymphocytes (TILs) – low TIL density may predict poorer long-term prognosis in T1 laryngeal cancer
35. Cell-in-cell phenomenon associates with aggressive characteristics and cancer-related mortality in early oral tongue cancer
36. Assessment of Tumor-infiltrating Lymphocytes Predicts the Behavior of Early-stage Oral Tongue Cancer
37. MicroRNA and protein profiles in invasive versus non-invasive oral tongue squamous cell carcinoma cells in vitro
38. Small oral tongue cancers (≤ 4 cm in diameter) with clinically negative neck: from the 7th to the 8th edition of the American Joint Committee on Cancer
39. Tumour budding in oral squamous cell carcinoma: a meta-analysis
40. Evaluation of the budding and depth of invasion (BD) model in oral tongue cancer biopsies
41. Programmed death-ligand 1 and tumor-infiltrating lymphocytes (TILs) – low TIL density may predict poorer long-term prognosis in T1 laryngeal cancer
42. Application of artificial intelligence for overall survival risk stratification in oropharyngeal carcinoma: A validation of ProgTOOL
43. A Proposal to Revise the Histopathologic Grading System of Early Oral Tongue Cancer Incorporating Tumor Budding
44. Interpretable machine learning model for prediction of overall survival in laryngeal cancer.
45. Prognostic significance of the neural invasion in oral squamous cell carcinoma
46. Advanced-stage tongue squamous cell carcinoma: a machine learning model for risk stratification and treatment planning
47. Prognostic markers for oral cancer: An overview of the current status and directions for future research
48. Clinical Significance of Overall Assessment of Tumor-Infiltrating Lymphocytes in Oropharyngeal Cancer: A Meta-analysis
49. Optimal cutoff point for depth of invasion in patient selection: A continuing debate
50. An interpretable machine learning prognostic system for risk stratification in oropharyngeal cancer
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