146 related articles for article (PubMed ID: 36946048)
1. [Construction and evaluation of an artificial intelligence-based risk prediction model for death in patients with nasopharyngeal cancer].
Zhang H; Lu J; Jiang C; Fang M
Nan Fang Yi Ke Da Xue Xue Bao; 2023 Feb; 43(2):271-279. PubMed ID: 36946048
[TBL] [Abstract][Full Text] [Related]
2. Prognosis viewing for nasopharyngeal carcinoma treated with intensity-modulated radiation therapy: application of nomogram and decision curve analysis.
Fei Z; Qiu X; Li M; Chen C; Li Y; Huang Y
Jpn J Clin Oncol; 2020 Feb; 50(2):159-168. PubMed ID: 31711182
[TBL] [Abstract][Full Text] [Related]
3. Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP.
Alabi RO; Elmusrati M; Leivo I; Almangush A; Mäkitie AA
Sci Rep; 2023 Jun; 13(1):8984. PubMed ID: 37268685
[TBL] [Abstract][Full Text] [Related]
4. A prediction model for xerostomia in locoregionally advanced nasopharyngeal carcinoma patients receiving radical radiotherapy.
Li M; Zhang J; Zha Y; Li Y; Hu B; Zheng S; Zhou J
BMC Oral Health; 2022 Jun; 22(1):239. PubMed ID: 35715856
[TBL] [Abstract][Full Text] [Related]
5. Nomograms-based prediction of overall and cancer-specific survivals for patients diagnosed with major salivary gland carcinoma.
Guo Z; Wang Z; Liu Y; Han J; Liu J; Zhang C
Ann Transl Med; 2021 Aug; 9(15):1230. PubMed ID: 34532367
[TBL] [Abstract][Full Text] [Related]
6. A novel model for predicting prognosis and response to immunotherapy in nasopharyngeal carcinoma patients.
Wu YX; Tian BY; Ou XY; Wu M; Huang Q; Han RK; He X; Chen SL
Cancer Immunol Immunother; 2024 Jan; 73(1):14. PubMed ID: 38236288
[TBL] [Abstract][Full Text] [Related]
7. Prognostic nomogram for patients with Nasopharyngeal Carcinoma incorporating hematological biomarkers and clinical characteristics.
Li J; Chen S; Peng S; Liu Y; Xing S; He X; Chen H
Int J Biol Sci; 2018; 14(5):549-556. PubMed ID: 29805306
[TBL] [Abstract][Full Text] [Related]
8. MRI-based radiomics nomogram for predicting temporal lobe injury after radiotherapy in nasopharyngeal carcinoma.
Hou J; Li H; Zeng B; Pang P; Ai Z; Li F; Lu Q; Yu X
Eur Radiol; 2022 Feb; 32(2):1106-1114. PubMed ID: 34467454
[TBL] [Abstract][Full Text] [Related]
9. Development and validation of a normal tissue complication probability model for acquired nasal cavity stenosis and atresia after radical radiotherapy for nasopharyngeal carcinoma.
Yan JJ; Guo SS; Lin DF; Liu LT; Liu SL; Xiao BB; Yang JH; Wen DX; Yang ZC; Liang YJ; Tang QN; Lin C; Li XY; Sun XS; Li JB; Tang LQ; Chen QY; Mai HQ
Radiother Oncol; 2021 Jul; 160():9-17. PubMed ID: 33839205
[TBL] [Abstract][Full Text] [Related]
10. A Simple Nomogram for Predicting Osteoarthritis Severity in Patients with Knee Osteoarthritis.
Zhang Q; Yao Y; Wang J; Chen Y; Ren D; Wang P
Comput Math Methods Med; 2022; 2022():3605369. PubMed ID: 36092788
[TBL] [Abstract][Full Text] [Related]
11. Application of a combined radiomics nomogram based on CE-CT in the preoperative prediction of thymomas risk categorization.
Dong W; Xiong S; Lei P; Wang X; Liu H; Liu Y; Zou H; Fan B; Qiu Y
Front Oncol; 2022; 12():944005. PubMed ID: 36081562
[TBL] [Abstract][Full Text] [Related]
12. Application Value of Magnetic Resonance Radiomics and Clinical Nomograms in Evaluating the Sensitivity of Neoadjuvant Chemotherapy for Nasopharyngeal Carcinoma.
Hu C; Zheng D; Cao X; Pang P; Fang Y; Lu T; Chen Y
Front Oncol; 2021; 11():740776. PubMed ID: 34790570
[TBL] [Abstract][Full Text] [Related]
13. The prognostic nutritional index represents a novel inflammation-nutrition-based prognostic factor for nasopharyngeal carcinoma.
Jiang YM; Huang ST; Pan XB; Ma JL; Zhu XD
Front Nutr; 2023; 10():1036572. PubMed ID: 36875852
[TBL] [Abstract][Full Text] [Related]
14. A Comparison of LASSO Regression and Tree-Based Models for Delayed Cerebral Ischemia in Elderly Patients With Subarachnoid Hemorrhage.
Hu P; Liu Y; Li Y; Guo G; Su Z; Gao X; Chen J; Qi Y; Xu Y; Yan T; Ye L; Sun Q; Deng G; Zhang H; Chen Q
Front Neurol; 2022; 13():791547. PubMed ID: 35359648
[TBL] [Abstract][Full Text] [Related]
15. A 5-year survival status prognosis of nonmetastatic cervical cancer patients through machine learning algorithms.
Yu W; Lu Y; Shou H; Xu H; Shi L; Geng X; Song T
Cancer Med; 2023 Mar; 12(6):6867-6876. PubMed ID: 36479910
[TBL] [Abstract][Full Text] [Related]
16. Development and validation of a risk prediction model for overall survival in patients with nasopharyngeal carcinoma: a prospective cohort study in China.
Miao S; Lei H; Li X; Zhou W; Wang G; Sun A; Wang Y; Wu Y
Cancer Cell Int; 2022 Nov; 22(1):360. PubMed ID: 36403013
[TBL] [Abstract][Full Text] [Related]
17. MRI-identified multidimensional nodal features predict survival and concurrent chemotherapy benefit for stage II nasopharyngeal carcinoma.
Liu Y; Zhang J; Wang J; Wu R; Huang X; Wang K; Qu Y; Chen X; Li Y; Zhang Y; Yi J
Radiol Oncol; 2022 Dec; 56(4):479-487. PubMed ID: 36503717
[TBL] [Abstract][Full Text] [Related]
18. Development of a Nomogram Model for Treatment of Nonmetastatic Nasopharyngeal Carcinoma.
Zhang LL; Xu F; Song D; Huang MY; Huang YS; Deng QL; Li YY; Shao JY
JAMA Netw Open; 2020 Dec; 3(12):e2029882. PubMed ID: 33306119
[TBL] [Abstract][Full Text] [Related]
19. Nomogram to Predict Long-Term Overall Survival and Cancer-Specific Survival of Radiotherapy Patients with Nasopharyngeal Carcinoma.
Li Z; Li C; Yang D; Zhou Z; Kang M
Biomed Res Int; 2023; 2023():7126881. PubMed ID: 36704722
[TBL] [Abstract][Full Text] [Related]
20. Construction of diagnostic and prognostic models based on gene signatures of nasopharyngeal carcinoma by machine learning methods.
Wang Y; He Y; Duan X; Pang H; Zhou P
Transl Cancer Res; 2023 May; 12(5):1254-1269. PubMed ID: 37304552
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]