668 related articles for article (PubMed ID: 35721715)
1. Extrathyroidal Extension Prediction of Papillary Thyroid Cancer With Computed Tomography Based Radiomics Nomogram: A Multicenter Study.
Yu P; Wu X; Li J; Mao N; Zhang H; Zheng G; Han X; Dong L; Che K; Wang Q; Li G; Mou Y; Song X
Front Endocrinol (Lausanne); 2022; 13():874396. PubMed ID: 35721715
[TBL] [Abstract][Full Text] [Related]
2. Development and Validation of a Computed Tomography-Based Radiomics Nomogram for the Preoperative Prediction of Central Lymph Node Metastasis in Papillary Thyroid Microcarcinoma.
Mou Y; Han X; Li J; Yu P; Wang C; Song Z; Wang X; Zhang M; Zhang H; Mao N; Song X
Acad Radiol; 2024 May; 31(5):1805-1817. PubMed ID: 38071100
[TBL] [Abstract][Full Text] [Related]
3. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
[TBL] [Abstract][Full Text] [Related]
4. CT Radiomics-Based Nomogram for Predicting the Lateral Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma: A Prospective Multicenter Study.
Dong L; Han X; Yu P; Zhang W; Wang C; Sun Q; Song F; Zhang H; Zheng G; Mao N; Song X
Acad Radiol; 2023 Dec; 30(12):3032-3046. PubMed ID: 37210266
[TBL] [Abstract][Full Text] [Related]
5. Radiomics Analysis of Computed Tomography for Prediction of Thyroid Capsule Invasion in Papillary Thyroid Carcinoma: A Multi-Classifier and Two-Center Study.
Wu X; Yu P; Jia C; Mao N; Che K; Li G; Zhang H; Mou Y; Song X
Front Endocrinol (Lausanne); 2022; 13():849065. PubMed ID: 35692398
[TBL] [Abstract][Full Text] [Related]
6. Iodine Maps from Dual-Energy CT to Predict Extrathyroidal Extension and Recurrence in Papillary Thyroid Cancer Based on a Radiomics Approach.
Xu XQ; Zhou Y; Su GY; Tao XW; Ge YQ; Si Y; Shen MP; Wu FY
AJNR Am J Neuroradiol; 2022 May; 43(5):748-755. PubMed ID: 35422420
[TBL] [Abstract][Full Text] [Related]
7. Analysis of preoperative computed tomography radiomics and clinical factors for predicting postsurgical recurrence of papillary thyroid carcinoma.
Xu H; Wu W; Zhao Y; Liu Z; Bao D; Li L; Lin M; Zhang Y; Zhao X; Luo D
Cancer Imaging; 2023 Dec; 23(1):118. PubMed ID: 38098119
[TBL] [Abstract][Full Text] [Related]
8. Nomogram Based on Shear-Wave Elastography Radiomics Can Improve Preoperative Cervical Lymph Node Staging for Papillary Thyroid Carcinoma.
Jiang M; Li C; Tang S; Lv W; Yi A; Wang B; Yu S; Cui X; Dietrich CF
Thyroid; 2020 Jun; 30(6):885-897. PubMed ID: 32027225
[No Abstract] [Full Text] [Related]
9. Radiomics from Primary Tumor on Dual-Energy CT Derived Iodine Maps can Predict Cervical Lymph Node Metastasis in Papillary Thyroid Cancer.
Zhou Y; Su GY; Hu H; Tao XW; Ge YQ; Si Y; Shen MP; Xu XQ; Wu FY
Acad Radiol; 2022 Mar; 29 Suppl 3():S222-S231. PubMed ID: 34366279
[TBL] [Abstract][Full Text] [Related]
10. Applying a nomogram based on preoperative CT to predict early recurrence of laryngeal squamous cell carcinoma after surgery.
Yao Y; Jia C; Zhang H; Mou Y; Wang C; Han X; Yu P; Mao N; Song X
J Xray Sci Technol; 2023; 31(3):435-452. PubMed ID: 36806538
[TBL] [Abstract][Full Text] [Related]
11. Predicting Extrathyroidal Extension in Papillary Thyroid Carcinoma Using a Clinical-Radiomics Nomogram Based on B-Mode and Contrast-Enhanced Ultrasound.
Jiang L; Guo S; Zhao Y; Cheng Z; Zhong X; Zhou P
Diagnostics (Basel); 2023 May; 13(10):. PubMed ID: 37238217
[TBL] [Abstract][Full Text] [Related]
12. Radiomics analysis of dual-energy CT-derived iodine maps for diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer.
Zhou Y; Su GY; Hu H; Ge YQ; Si Y; Shen MP; Xu XQ; Wu FY
Eur Radiol; 2020 Nov; 30(11):6251-6262. PubMed ID: 32500193
[TBL] [Abstract][Full Text] [Related]
13. Three-dimensional ultrasound-based radiomics nomogram for the prediction of extrathyroidal extension features in papillary thyroid cancer.
Lu WJ; Mao L; Li J; OuYang LY; Chen JY; Chen SY; Lin YY; Wu YW; Chen SN; Qiu SD; Chen F
Front Oncol; 2023; 13():1046951. PubMed ID: 37681026
[TBL] [Abstract][Full Text] [Related]
14. Preoperative prediction of extrathyroidal extension: radiomics signature based on multimodal ultrasound to papillary thyroid carcinoma.
Wan F; He W; Zhang W; Zhang Y; Zhang H; Guang Y
BMC Med Imaging; 2023 Jul; 23(1):96. PubMed ID: 37474935
[TBL] [Abstract][Full Text] [Related]
15. A computed tomography-based radiomic nomogram for predicting lymph node metastasis in patients with early-stage papillary thyroid carcinoma.
Lai L; Guan Q; Liang Y; Chen J; Liao Y; Xu H; Wei X
Acta Radiol; 2022 Sep; 63(9):1187-1195. PubMed ID: 34859689
[TBL] [Abstract][Full Text] [Related]
16. A radiomics nomogram for the ultrasound-based evaluation of central cervical lymph node metastasis in papillary thyroid carcinoma.
Wen Q; Wang Z; Traverso A; Liu Y; Xu R; Feng Y; Qian L
Front Endocrinol (Lausanne); 2022; 13():1064434. PubMed ID: 36531493
[TBL] [Abstract][Full Text] [Related]
17. Radiomics based on multiparametric MRI for extrathyroidal extension feature prediction in papillary thyroid cancer.
Wei R; Wang H; Wang L; Hu W; Sun X; Dai Z; Zhu J; Li H; Ge Y; Song B
BMC Med Imaging; 2021 Feb; 21(1):20. PubMed ID: 33563233
[TBL] [Abstract][Full Text] [Related]
18. Preoperative prediction for lauren type of gastric cancer: A radiomics nomogram analysis based on CT images and clinical features.
Sun Z; Jin L; Zhang S; Duan S; Xing W; Hu S
J Xray Sci Technol; 2021; 29(4):675-686. PubMed ID: 34024809
[TBL] [Abstract][Full Text] [Related]
19. Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma.
Deng PZ; Zhao BG; Huang XH; Xu TF; Chen ZJ; Wei QF; Liu XY; Guo YQ; Yuan SG; Liao WJ
World J Gastroenterol; 2022 Aug; 28(31):4376-4389. PubMed ID: 36159012
[TBL] [Abstract][Full Text] [Related]
20. Ultrasound images-based deep learning radiomics nomogram for preoperative prediction of
Yu J; Zhang Y; Zheng J; Jia M; Lu X
Front Endocrinol (Lausanne); 2022; 13():1062571. PubMed ID: 36605945
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
