145 related articles for article (PubMed ID: 35021182)
1. Machine Learning Algorithms as a Computer-Assisted Decision Tool for Oral Cancer Prognosis and Management Decisions: A Systematic Review.
Chiesa-Estomba CM; Graña M; Medela A; Sistiaga-Suarez JA; Lechien JR; Calvo-Henriquez C; Mayo-Yanez M; Vaira LA; Grammatica A; Cammaroto G; Ayad T; Fagan JJ
ORL J Otorhinolaryngol Relat Spec; 2022; 84(4):278-288. PubMed ID: 35021182
[TBL] [Abstract][Full Text] [Related]
2. Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future-A systematic review.
Alabi RO; Youssef O; Pirinen M; Elmusrati M; Mäkitie AA; Leivo I; Almangush A
Artif Intell Med; 2021 May; 115():102060. PubMed ID: 34001326
[TBL] [Abstract][Full Text] [Related]
3. Machine learning to predict occult nodal metastasis in early oral squamous cell carcinoma.
Bur AM; Holcomb A; Goodwin S; Woodroof J; Karadaghy O; Shnayder Y; Kakarala K; Brant J; Shew M
Oral Oncol; 2019 May; 92():20-25. PubMed ID: 31010618
[TBL] [Abstract][Full Text] [Related]
4. Prediction models applying machine learning to oral cavity cancer outcomes: A systematic review.
Adeoye J; Tan JY; Choi SW; Thomson P
Int J Med Inform; 2021 Oct; 154():104557. PubMed ID: 34455119
[TBL] [Abstract][Full Text] [Related]
5. Comparison of machine learning algorithms for the prediction of five-year survival in oral squamous cell carcinoma.
Alkhadar H; Macluskey M; White S; Ellis I; Gardner A
J Oral Pathol Med; 2021 Apr; 50(4):378-384. PubMed ID: 33220109
[TBL] [Abstract][Full Text] [Related]
6. What has the National Cancer Database taught us about oral cavity squamous cell carcinoma?
Graillon N; Iocca O; Carey RM; Benjamin K; Cannady SB; Hartner L; Newman JG; Rajasekaran K; Brant JA; Shanti RM
Int J Oral Maxillofac Surg; 2022 Jan; 51(1):10-17. PubMed ID: 33840565
[TBL] [Abstract][Full Text] [Related]
7. Clinicopathological and immunohistochemical evaluation of oral and oropharyngeal squamous cell carcinoma in Chilean population.
Rivera C; González-Arriagada WA; Loyola-Brambilla M; de Almeida OP; Coletta RD; Venegas B
Int J Clin Exp Pathol; 2014; 7(9):5968-77. PubMed ID: 25337241
[TBL] [Abstract][Full Text] [Related]
8. Comparison of time-to-event machine learning models in predicting oral cavity cancer prognosis.
Adeoye J; Hui L; Koohi-Moghadam M; Tan JY; Choi SW; Thomson P
Int J Med Inform; 2022 Jan; 157():104635. PubMed ID: 34800847
[TBL] [Abstract][Full Text] [Related]
9. Use of artificial intelligence in diagnosis of head and neck precancerous and cancerous lesions: A systematic review.
Mahmood H; Shaban M; Indave BI; Santos-Silva AR; Rajpoot N; Khurram SA
Oral Oncol; 2020 Nov; 110():104885. PubMed ID: 32674040
[TBL] [Abstract][Full Text] [Related]
10. Machine learning and treatment outcome prediction for oral cancer.
Chu CS; Lee NP; Adeoye J; Thomson P; Choi SW
J Oral Pathol Med; 2020 Nov; 49(10):977-985. PubMed ID: 32740951
[TBL] [Abstract][Full Text] [Related]
11. Predicting Overall Survival Using Machine Learning Algorithms in Oral Cavity Squamous Cell Carcinoma.
Tan JY; Adeoye J; Thomson P; Sharma D; Ramamurthy P; Choi SW
Anticancer Res; 2022 Dec; 42(12):5859-5866. PubMed ID: 36456152
[TBL] [Abstract][Full Text] [Related]
12. Identification and validation of seven RNA binding protein genes as a prognostic signature in oral cavity squamous cell carcinoma.
Huang Z; Lan T; Wang J; Chen Z; Zhang X
Bioengineered; 2021 Dec; 12(1):7248-7262. PubMed ID: 34585646
[TBL] [Abstract][Full Text] [Related]
13. Histopathologic Oral Cancer Prediction Using Oral Squamous Cell Carcinoma Biopsy Empowered with Transfer Learning.
Rahman AU; Alqahtani A; Aldhafferi N; Nasir MU; Khan MF; Khan MA; Mosavi A
Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632242
[TBL] [Abstract][Full Text] [Related]
14. Proceedings of the North American Society of Head and Neck Pathology Companion Meeting, New Orleans, LA, March 12, 2023: Oral Cavity Dysplasia: Why Does Histologic Grading Continue to be Contentious?
Wolk R; Lingen MW
Head Neck Pathol; 2023 Jun; 17(2):292-298. PubMed ID: 37184731
[TBL] [Abstract][Full Text] [Related]
15. Genetic aberrations in oral or head and neck squamous cell carcinoma 3: clinico-pathological applications.
Scully C; Field JK; Tanzawa H
Oral Oncol; 2000 Sep; 36(5):404-13. PubMed ID: 10964046
[TBL] [Abstract][Full Text] [Related]
16. A machine learning model for predicting the three-year survival status of patients with hypopharyngeal squamous cell carcinoma using multiple parameters.
Li Z; Ding S; Zhong Q; Fang J; Huang J; Huang Z; Zhang Y
J Laryngol Otol; 2023 Sep; 137(9):1041-1047. PubMed ID: 36682376
[TBL] [Abstract][Full Text] [Related]
17. Prediction of the treatment outcome using machine learning with FDG-PET image-based multiparametric approach in patients with oral cavity squamous cell carcinoma.
Fujima N; Andreu-Arasa VC; Meibom SK; Mercier GA; Salama AR; Truong MT; Sakai O
Clin Radiol; 2021 Sep; 76(9):711.e1-711.e7. PubMed ID: 33934877
[TBL] [Abstract][Full Text] [Related]
18. Treatment delays in oral cavity squamous cell carcinoma and association with survival.
Fujiwara RJ; Judson BL; Yarbrough WG; Husain Z; Mehra S
Head Neck; 2017 Apr; 39(4):639-646. PubMed ID: 28236349
[TBL] [Abstract][Full Text] [Related]
19. Systematic review and individual patient data analysis of pediatric head and neck squamous cell carcinoma: An analysis of 217 cases.
Bhanu Prasad V; Mallick S; Upadhyay AD; Rath GK
Int J Pediatr Otorhinolaryngol; 2017 Jan; 92():75-81. PubMed ID: 28012539
[TBL] [Abstract][Full Text] [Related]
20. Oral and Oropharyngeal squamous cell carcinoma: prognostic and predictive parameters in the etiopathogenetic route.
Panarese I; Aquino G; Ronchi A; Longo F; Montella M; Cozzolino I; Roccuzzo G; Colella G; Caraglia M; Franco R
Expert Rev Anticancer Ther; 2019 Feb; 19(2):105-119. PubMed ID: 30582397
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
