122 related articles for article (PubMed ID: 38905878)
1. Diagnostic accuracy of CT-based radiomics and deep learning for predicting lymph node metastasis in esophageal cancer.
Jannatdoust P; Valizadeh P; Pahlevan-Fallahy MT; Hassankhani A; Amoukhteh M; Behrouzieh S; Ghadimi DJ; Bilgin C; Gholamrezanezhad A
Clin Imaging; 2024 Jun; 113():110225. PubMed ID: 38905878
[TBL] [Abstract][Full Text] [Related]
2. Radiomics diagnostic performance for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis.
Ma D; Zhou T; Chen J; Chen J
BMC Med Imaging; 2024 Jun; 24(1):144. PubMed ID: 38867143
[TBL] [Abstract][Full Text] [Related]
3. Radiomics and deep learning models for CT pre-operative lymph node staging in pancreatic ductal adenocarcinoma: A systematic review and meta-analysis.
Castellana R; Fanni SC; Roncella C; Romei C; Natrella M; Neri E
Eur J Radiol; 2024 Jul; 176():111510. PubMed ID: 38781919
[TBL] [Abstract][Full Text] [Related]
4. Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer.
Li J; Dong D; Fang M; Wang R; Tian J; Li H; Gao J
Eur Radiol; 2020 Apr; 30(4):2324-2333. PubMed ID: 31953668
[TBL] [Abstract][Full Text] [Related]
5. CT radiomics features to predict lymph node metastasis in advanced esophageal squamous cell carcinoma and to discriminate between regional and non-regional lymph node metastasis: a case control study.
Ou J; Wu L; Li R; Wu CQ; Liu J; Chen TW; Zhang XM; Tang S; Wu YP; Yang LQ; Tan BG; Lu FL
Quant Imaging Med Surg; 2021 Feb; 11(2):628-640. PubMed ID: 33532263
[TBL] [Abstract][Full Text] [Related]
6. Comparing three-dimensional and two-dimensional deep-learning, radiomics, and fusion models for predicting occult lymph node metastasis in laryngeal squamous cell carcinoma based on CT imaging: a multicentre, retrospective, diagnostic study.
Wang W; Liang H; Zhang Z; Xu C; Wei D; Li W; Qian Y; Zhang L; Liu J; Lei D
EClinicalMedicine; 2024 Jan; 67():102385. PubMed ID: 38261897
[TBL] [Abstract][Full Text] [Related]
7. Predictive value of radiomic features extracted from primary lung adenocarcinoma in forecasting thoracic lymph node metastasis: a systematic review and meta-analysis.
Wu T; Gao C; Lou X; Wu J; Xu M; Wu L
BMC Pulm Med; 2024 May; 24(1):246. PubMed ID: 38762472
[TBL] [Abstract][Full Text] [Related]
8. Diagnostic performance of CT scan-based radiomics for prediction of lymph node metastasis in gastric cancer: a systematic review and meta-analysis.
HajiEsmailPoor Z; Tabnak P; Baradaran B; Pashazadeh F; Aghebati-Maleki L
Front Oncol; 2023; 13():1185663. PubMed ID: 37936604
[TBL] [Abstract][Full Text] [Related]
9. Application of radiomics for preoperative prediction of lymph node metastasis in colorectal cancer: a systematic review and meta-analysis.
Abbaspour E; Karimzadhagh S; Monsef A; Joukar F; Mansour-Ghanaei F; Hassanipour S
Int J Surg; 2024 Jun; 110(6):3795-3813. PubMed ID: 38935817
[TBL] [Abstract][Full Text] [Related]
10. CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis.
Liu L; Liao H; Zhao Y; Yin J; Wang C; Duan L; Xie P; Wei W; Xu M; Su D
Front Oncol; 2024; 14():1267596. PubMed ID: 38577325
[TBL] [Abstract][Full Text] [Related]
11. Predictive nomogram for lymph node metastasis and survival in gastric cancer using contrast-enhanced computed tomography-based radiomics: a retrospective study.
Zhang W; Wang S; Dong Q; Chen W; Wang P; Zhu G; Chen X; Cai Y
PeerJ; 2024; 12():e17111. PubMed ID: 38525272
[TBL] [Abstract][Full Text] [Related]
12. CT radiomics based on the peritumoral adipose region of gastric adenocarcinoma for preoperative prediction of lymph node metastasis.
Ding XM; Zhou HY; Wang YS; Cao JM; Ou J; Zhang XM; Chen TW
Eur J Radiol; 2024 Jun; 175():111479. PubMed ID: 38663124
[TBL] [Abstract][Full Text] [Related]
13. Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.
Zhang H; Liao M; Guo Q; Chen J; Wang S; Liu S; Xiao F
Med Phys; 2023 Apr; 50(4):2049-2060. PubMed ID: 36563341
[TBL] [Abstract][Full Text] [Related]
14.
Xue XQ; Yu WJ; Shi X; Shao XL; Wang YT
Front Oncol; 2022; 12():911168. PubMed ID: 36003788
[TBL] [Abstract][Full Text] [Related]
15. [The value of spectral CT-based radiomics in preoperative prediction of lymph node metastasis of advanced gastric cancer].
Wang R; Li J; Fang MJ; Dong D; Liang P; Gao JB
Zhonghua Yi Xue Za Zhi; 2020 Jun; 100(21):1617-1622. PubMed ID: 32486595
[No Abstract] [Full Text] [Related]
16. 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]
17. Radiomics diagnostic performance in predicting lymph node metastasis of papillary thyroid carcinoma: A systematic review and meta-analysis.
HajiEsmailPoor Z; Kargar Z; Tabnak P
Eur J Radiol; 2023 Nov; 168():111129. PubMed ID: 37820522
[TBL] [Abstract][Full Text] [Related]
18. Radiomics for differentiating tumor deposits from lymph node metastasis in rectal cancer.
Zhang YC; Li M; Jin YM; Xu JX; Huang CC; Song B
World J Gastroenterol; 2022 Aug; 28(29):3960-3970. PubMed ID: 36157536
[TBL] [Abstract][Full Text] [Related]
19. Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.
Ma X; Xia L; Chen J; Wan W; Zhou W
Eur Radiol; 2023 Mar; 33(3):1949-1962. PubMed ID: 36169691
[TBL] [Abstract][Full Text] [Related]
20. Diagnostic performance of radiomics in predicting axillary lymph node metastasis in breast cancer: A systematic review and meta-analysis.
Gong X; Guo Y; Zhu T; Peng X; Xing D; Zhang M
Front Oncol; 2022; 12():1046005. PubMed ID: 36518318
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
