219 related articles for article (PubMed ID: 38151672)
1. A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma.
Chen Z; Yu Y; Liu S; Du W; Hu L; Wang C; Li J; Liu J; Zhang W; Peng X
Clin Oral Investig; 2023 Dec; 28(1):39. PubMed ID: 38151672
[TBL] [Abstract][Full Text] [Related]
2. Nodal-based radiomics analysis for identifying cervical lymph node metastasis at levels I and II in patients with oral squamous cell carcinoma using contrast-enhanced computed tomography.
Tomita H; Yamashiro T; Heianna J; Nakasone T; Kimura Y; Mimura H; Murayama S
Eur Radiol; 2021 Oct; 31(10):7440-7449. PubMed ID: 33787970
[TBL] [Abstract][Full Text] [Related]
3. Diagnosing cervical lymph node metastasis in oral squamous cell carcinoma based on third-generation dual-source, dual-energy computed tomography.
Luo YH; Mei XL; Liu QR; Jiang B; Zhang S; Zhang K; Wu X; Luo YM; Li YJ
Eur Radiol; 2023 Jan; 33(1):162-171. PubMed ID: 36070090
[TBL] [Abstract][Full Text] [Related]
4. Diagnostic accuracy of contrast-enhanced computed tomography in assessing cervical lymph node status in patients with oral squamous cell carcinoma.
Struckmeier AK; Yekta E; Agaimy A; Kopp M; Buchbender M; Moest T; Lutz R; Kesting M
J Cancer Res Clin Oncol; 2023 Dec; 149(19):17437-17450. PubMed ID: 37875746
[TBL] [Abstract][Full Text] [Related]
5. Diagnostic value of magnetic resonance imaging in cervical lymph node metastasis of oral squamous cell carcinoma.
Wang Y; Mao M; Li J; Feng Z; Qin L; Han Z
Oral Surg Oral Med Oral Pathol Oral Radiol; 2022 May; 133(5):582-592. PubMed ID: 34953758
[TBL] [Abstract][Full Text] [Related]
6. Radiomics from dual-energy CT-derived iodine maps predict lymph node metastasis in head and neck squamous cell carcinoma.
Zhang W; Liu J; Jin W; Li R; Xie X; Zhao W; Xia S; Han D
Radiol Med; 2024 Feb; 129(2):252-267. PubMed ID: 38015363
[TBL] [Abstract][Full Text] [Related]
7. Radiomics analysis of CT imaging improves preoperative prediction of cervical lymph node metastasis in laryngeal squamous cell carcinoma.
Zhao X; Li W; Zhang J; Tian S; Zhou Y; Xu X; Hu H; Lei D; Wu F
Eur Radiol; 2023 Feb; 33(2):1121-1131. PubMed ID: 35984515
[TBL] [Abstract][Full Text] [Related]
8. Prediction of Individual Lymph Node Metastatic Status in Esophageal Squamous Cell Carcinoma Using Routine Computed Tomography Imaging: Comparison of Size-Based Measurements and Radiomics-Based Models.
Xie C; Hu Y; Han L; Fu J; Vardhanabhuti V; Yang H
Ann Surg Oncol; 2022 Dec; 29(13):8117-8126. PubMed ID: 36018524
[TBL] [Abstract][Full Text] [Related]
9. Noninvasive prediction of lymph node status for patients with early-stage cervical cancer based on radiomics features from ultrasound images.
Jin X; Ai Y; Zhang J; Zhu H; Jin J; Teng Y; Chen B; Xie C
Eur Radiol; 2020 Jul; 30(7):4117-4124. PubMed ID: 32078013
[TBL] [Abstract][Full Text] [Related]
10. Comparison of Traditional Radiomics, Deep Learning Radiomics and Fusion Methods for Axillary Lymph Node Metastasis Prediction in Breast Cancer.
Li X; Yang L; Jiao X
Acad Radiol; 2023 Jul; 30(7):1281-1287. PubMed ID: 36376154
[TBL] [Abstract][Full Text] [Related]
11. Deep learning assisted contrast-enhanced CT-based diagnosis of cervical lymph node metastasis of oral cancer: a retrospective study of 1466 cases.
Xu X; Xi L; Wei L; Wu L; Xu Y; Liu B; Li B; Liu K; Hou G; Lin H; Shao Z; Su K; Shang Z
Eur Radiol; 2023 Jun; 33(6):4303-4312. PubMed ID: 36576543
[TBL] [Abstract][Full Text] [Related]
12. Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.
Deng Z; Liu X; Wu R; Yan H; Gou L; Hu W; Wan J; Song C; Chen J; Ma D; Zhou H; Tian D
BMC Cancer; 2024 Apr; 24(1):536. PubMed ID: 38678211
[TBL] [Abstract][Full Text] [Related]
13. Pre-operative contrast enhanced computer tomographic evaluation of cervical nodal metastatic disease in oral squamous cell carcinoma.
Pandeshwar P; Jayanthi K; Raghuram P
Indian J Cancer; 2013; 50(4):310-5. PubMed ID: 24369206
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Automatic detection of cervical lymph nodes in patients with oral squamous cell carcinoma using a deep learning technique: a preliminary study.
Ariji Y; Fukuda M; Nozawa M; Kuwada C; Goto M; Ishibashi K; Nakayama A; Sugita Y; Nagao T; Ariji E
Oral Radiol; 2021 Apr; 37(2):290-296. PubMed ID: 32506212
[TBL] [Abstract][Full Text] [Related]
16. Lymph node metastasis prediction and biological pathway associations underlying DCE-MRI deep learning radiomics in invasive breast cancer.
Liu W; Chen W; Xia J; Lu Z; Fu Y; Li Y; Tan Z
BMC Med Imaging; 2024 Apr; 24(1):91. PubMed ID: 38627678
[TBL] [Abstract][Full Text] [Related]
17. Deep learning combined with radiomics for the classification of enlarged cervical lymph nodes.
Zhang W; Peng J; Zhao S; Wu W; Yang J; Ye J; Xu S
J Cancer Res Clin Oncol; 2022 Oct; 148(10):2773-2780. PubMed ID: 35562596
[TBL] [Abstract][Full Text] [Related]
18. A preoperative radiomics model for the identification of lymph node metastasis in patients with early-stage cervical squamous cell carcinoma.
Yan L; Yao H; Long R; Wu L; Xia H; Li J; Liu Z; Liang C
Br J Radiol; 2020 Dec; 93(1116):20200358. PubMed ID: 32960673
[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. Detection of cervical lymph node metastasis from oral cavity cancer using a non-radiating, noninvasive digital infrared thermal imaging system.
Dong F; Tao C; Wu J; Su Y; Wang Y; Wang Y; Guo C; Lyu P
Sci Rep; 2018 May; 8(1):7219. PubMed ID: 29739969
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]