152 related articles for article (PubMed ID: 34359623)
1. Site-Specific Variation in Radiomic Features of Head and Neck Squamous Cell Carcinoma and Its Impact on Machine Learning Models.
Liu X; Maleki F; Muthukrishnan N; Ovens K; Huang SH; Pérez-Lara A; Romero-Sanchez G; Bhatnagar SR; Chatterjee A; Pusztaszeri MP; Spatz A; Batist G; Payabvash S; Haider SP; Mahajan A; Reinhold C; Forghani B; O'Sullivan B; Yu E; Forghani R
Cancers (Basel); 2021 Jul; 13(15):. PubMed ID: 34359623
[TBL] [Abstract][Full Text] [Related]
2. Radiomic analysis identifies tumor subtypes associated with distinct molecular and microenvironmental factors in head and neck squamous cell carcinoma.
Katsoulakis E; Yu Y; Apte AP; Leeman JE; Katabi N; Morris L; Deasy JO; Chan TA; Lee NY; Riaz N; Hatzoglou V; Oh JH
Oral Oncol; 2020 Nov; 110():104877. PubMed ID: 32619927
[TBL] [Abstract][Full Text] [Related]
3. Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures.
Mes SW; van Velden FHP; Peltenburg B; Peeters CFW; Te Beest DE; van de Wiel MA; Mekke J; Mulder DC; Martens RM; Castelijns JA; Pameijer FA; de Bree R; Boellaard R; Leemans CR; Brakenhoff RH; de Graaf P
Eur Radiol; 2020 Nov; 30(11):6311-6321. PubMed ID: 32500196
[TBL] [Abstract][Full Text] [Related]
4. Computed tomography-derived radiomic signature of head and neck squamous cell carcinoma (peri)tumoral tissue for the prediction of locoregional recurrence and distant metastasis after concurrent chemo-radiotherapy.
Keek S; Sanduleanu S; Wesseling F; de Roest R; van den Brekel M; van der Heijden M; Vens C; Giuseppina C; Licitra L; Scheckenbach K; Vergeer M; Leemans CR; Brakenhoff RH; Nauta I; Cavalieri S; Woodruff HC; Poli T; Leijenaar R; Hoebers F; Lambin P
PLoS One; 2020; 15(5):e0232639. PubMed ID: 32442178
[TBL] [Abstract][Full Text] [Related]
5. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
[TBL] [Abstract][Full Text] [Related]
6. Imaging-Genomic Study of Head and Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes and Genomic Mechanisms via Integration of The Cancer Genome Atlas and The Cancer Imaging Archive.
Zhu Y; Mohamed ASR; Lai SY; Yang S; Kanwar A; Wei L; Kamal M; Sengupta S; Elhalawani H; Skinner H; Mackin DS; Shiao J; Messer J; Wong A; Ding Y; Zhang L; Court L; Ji Y; Fuller CD
JCO Clin Cancer Inform; 2019 Feb; 3():1-9. PubMed ID: 30730765
[TBL] [Abstract][Full Text] [Related]
7. Computed Tomography Radiomics Predicts HPV Status and Local Tumor Control After Definitive Radiochemotherapy in Head and Neck Squamous Cell Carcinoma.
Bogowicz M; Riesterer O; Ikenberg K; Stieb S; Moch H; Studer G; Guckenberger M; Tanadini-Lang S
Int J Radiat Oncol Biol Phys; 2017 Nov; 99(4):921-928. PubMed ID: 28807534
[TBL] [Abstract][Full Text] [Related]
8. CT-based Radiomic Signatures for Predicting Histopathologic Features in Head and Neck Squamous Cell Carcinoma.
Mukherjee P; Cintra M; Huang C; Zhou M; Zhu S; Colevas AD; Fischbein N; Gevaert O
Radiol Imaging Cancer; 2020 May; 2(3):e190039. PubMed ID: 32550599
[TBL] [Abstract][Full Text] [Related]
9. Development and validation of radiomic signatures of head and neck squamous cell carcinoma molecular features and subtypes.
Huang C; Cintra M; Brennan K; Zhou M; Colevas AD; Fischbein N; Zhu S; Gevaert O
EBioMedicine; 2019 Jul; 45():70-80. PubMed ID: 31255659
[TBL] [Abstract][Full Text] [Related]
10. A Radiomics Approach to Identify Immunologically Active Tumor in Patients with Head and Neck Squamous Cell Carcinomas.
Nguyen TM; Bertolus C; Giraud P; Burgun A; Saintigny P; Bibault JE; Foy JP
Cancers (Basel); 2023 Nov; 15(22):. PubMed ID: 38001629
[TBL] [Abstract][Full Text] [Related]
11. Utility of adding Radiomics to clinical features in predicting the outcomes of radiotherapy for head and neck cancer using machine learning.
Gangil T; Sharan K; Rao BD; Palanisamy K; Chakrabarti B; Kadavigere R
PLoS One; 2022; 17(12):e0277168. PubMed ID: 36520945
[TBL] [Abstract][Full Text] [Related]
12. Application of radiomics for the prediction of HPV status for patients with head and neck cancers.
Bagher-Ebadian H; Lu M; Siddiqui F; Ghanem AI; Wen N; Wu Q; Liu C; Movsas B; Chetty IJ
Med Phys; 2020 Feb; 47(2):563-575. PubMed ID: 31853980
[TBL] [Abstract][Full Text] [Related]
13. Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer.
Noortman WA; Aide N; Vriens D; Arkes LS; Slump CH; Boellaard R; Goeman JJ; Deroose CM; Machiels JP; Licitra LF; Lhommel R; Alessi A; Woff E; Goffin K; Le Tourneau C; Gal J; Temam S; Delord JP; van Velden FHP; de Geus-Oei LF
Cancers (Basel); 2023 May; 15(10):. PubMed ID: 37345017
[TBL] [Abstract][Full Text] [Related]
14. Technical note: On the development of an outcome-driven frequency filter for improving radiomics-based modeling of human papillomavirus (HPV) in patients with oropharyngeal squamous cell carcinoma.
Bagher-Ebadian H; Zhu S; Siddiqui F; Lu M; Movsas B; Chetty IJ
Med Phys; 2021 Nov; 48(11):7552-7562. PubMed ID: 34390003
[TBL] [Abstract][Full Text] [Related]
15. Comparison of PET and CT radiomics for prediction of local tumor control in head and neck squamous cell carcinoma.
Bogowicz M; Riesterer O; Stark LS; Studer G; Unkelbach J; Guckenberger M; Tanadini-Lang S
Acta Oncol; 2017 Nov; 56(11):1531-1536. PubMed ID: 28820287
[TBL] [Abstract][Full Text] [Related]
16. MRI-based radiomic signature as predictive marker for patients with head and neck squamous cell carcinoma.
Yuan Y; Ren J; Shi Y; Tao X
Eur J Radiol; 2019 Aug; 117():193-198. PubMed ID: 31307647
[TBL] [Abstract][Full Text] [Related]
17. Head and neck squamous cell carcinoma: prediction of cervical lymph node metastasis by dual-energy CT texture analysis with machine learning.
Forghani R; Chatterjee A; Reinhold C; Pérez-Lara A; Romero-Sanchez G; Ueno Y; Bayat M; Alexander JWM; Kadi L; Chankowsky J; Seuntjens J; Forghani B
Eur Radiol; 2019 Nov; 29(11):6172-6181. PubMed ID: 30980127
[TBL] [Abstract][Full Text] [Related]
18. Improved outcome prediction of oropharyngeal cancer by combining clinical and MRI features in machine learning models.
Bos P; van den Brekel MWM; Gouw ZAR; Al-Mamgani A; Taghavi M; Waktola S; Aerts HJWL; Castelijns JA; Beets-Tan RGH; Jasperse B
Eur J Radiol; 2021 Jun; 139():109701. PubMed ID: 33865064
[TBL] [Abstract][Full Text] [Related]
19. Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer.
Parmar C; Grossmann P; Rietveld D; Rietbergen MM; Lambin P; Aerts HJ
Front Oncol; 2015; 5():272. PubMed ID: 26697407
[TBL] [Abstract][Full Text] [Related]
20. Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI.
Sohn B; Choi YS; Ahn SS; Kim H; Han K; Lee SK; Kim J
Laryngoscope; 2021 Mar; 131(3):E851-E856. PubMed ID: 33070337
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]