144 related articles for article (PubMed ID: 37648970)
21. Using Machine Learning Methods to Assess Lymphovascular Invasion and Survival in Breast Cancer: Performance of Combining Preoperative Clinical and MRI Characteristics.
Xu Z; Xie Y; Wu L; Chen M; Shi Z; Cui Y; Han C; Lin H; Liu Y; Li P; Chen X; Ding Y; Liu Z
J Magn Reson Imaging; 2023 Nov; 58(5):1580-1589. PubMed ID: 36797654
[TBL] [Abstract][Full Text] [Related]
22. Radiomics Analysis to Predict Lymphovascular Invasion of Gastric Cancer Based on Iodine-Based Material Decomposition Images and Virtual Monoenergetic Images.
Shi C; Yan J; Yu Y; Hu C
J Comput Assist Tomogr; 2024 Mar-Apr 01; 48(2):175-183. PubMed ID: 38110306
[TBL] [Abstract][Full Text] [Related]
23. Preoperative prediction of lymphovascular invasion of colorectal cancer by radiomics based on 18F-FDG PET-CT and clinical factors.
Yang Y; Wei H; Fu F; Wei W; Wu Y; Bai Y; Li Q; Wang M
Front Radiol; 2023; 3():1212382. PubMed ID: 37614530
[TBL] [Abstract][Full Text] [Related]
24. ABVS-Based Radiomics for Early Predicting the Efficacy of Neoadjuvant Chemotherapy in Patients with Breast Cancers.
Jiang W; Deng X; Zhu T; Fang J; Li J
Breast Cancer (Dove Med Press); 2023; 15():625-636. PubMed ID: 37600669
[TBL] [Abstract][Full Text] [Related]
25. Computed tomography-based radiomics analysis to predict lymphovascular invasion in esophageal squamous cell carcinoma.
Peng H; Yang Q; Xue T; Chen Q; Li M; Duan S; Cai B; Feng F
Br J Radiol; 2022 Feb; 95(1130):20210918. PubMed ID: 34908477
[TBL] [Abstract][Full Text] [Related]
26. CT-based radiomics nomogram for the pre-operative prediction of lymphovascular invasion in colorectal cancer: a multicenter study.
Li M; Gu H; Xue T; Peng H; Chen Q; Zhu X; Duan S; Feng F
Br J Radiol; 2023 Jan; 96(1141):20220568. PubMed ID: 36318241
[TBL] [Abstract][Full Text] [Related]
27. Radiomics Analysis of Breast Lesions in Combination with Coronal Plane of ABVS and Strain Elastography.
Ma Q; Shen C; Gao Y; Duan Y; Li W; Lu G; Qin X; Zhang C; Wang J
Breast Cancer (Dove Med Press); 2023; 15():381-390. PubMed ID: 37260586
[TBL] [Abstract][Full Text] [Related]
28. [Value of the application of enhanced CT radiomics and machine learning in preoperative prediction of microvascular invasion in hepatocellular carcinoma].
Yu YX; Hu CH; Wang XM; Fan YF; Hu MJ; Shi C; Hu S; Zhu M; Zhang Y
Zhonghua Yi Xue Za Zhi; 2021 May; 101(17):1239-1245. PubMed ID: 34865392
[No Abstract] [Full Text] [Related]
29. Radiomics analysis of contrast-enhanced CT predicts lymphovascular invasion and disease outcome in gastric cancer: a preliminary study.
Chen X; Yang Z; Yang J; Liao Y; Pang P; Fan W; Chen X
Cancer Imaging; 2020 Apr; 20(1):24. PubMed ID: 32248822
[TBL] [Abstract][Full Text] [Related]
30.
Wang J; Zheng Z; Zhang Y; Tan W; Li J; Xing L; Sun X
Front Oncol; 2023; 13():1185808. PubMed ID: 37546415
[TBL] [Abstract][Full Text] [Related]
31. An endorectal ultrasound-based radiomics signature for preoperative prediction of lymphovascular invasion of rectal cancer.
Wu YQ; Gao RZ; Lin P; Wen R; Li HY; Mou MY; Chen FH; Huang F; Zhou WJ; Yang H; He Y; Wu J
BMC Med Imaging; 2022 May; 22(1):84. PubMed ID: 35538520
[TBL] [Abstract][Full Text] [Related]
32. Non-invasive Assessment of Axillary Lymph Node Metastasis Risk in Early Invasive Breast Cancer Adopting Automated Breast Volume Scanning-Based Radiomics Nomogram: A Multicenter Study.
Wang H; Yang XW; Chen F; Qin YY; Li XB; Ma SM; Lei JQ; Nan CL; Zhang WY; Chen W; Guo SL
Ultrasound Med Biol; 2023 May; 49(5):1202-1211. PubMed ID: 36746744
[TBL] [Abstract][Full Text] [Related]
33. Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using
Yang L; Chu W; Li M; Xu P; Wang M; Peng M; Wang K; Zhang L
Front Oncol; 2022; 12():836098. PubMed ID: 35433451
[TBL] [Abstract][Full Text] [Related]
34. Radiomics Signatures Based on Multiparametric MRI for the Preoperative Prediction of the HER2 Status of Patients with Breast Cancer.
Zhou J; Tan H; Li W; Liu Z; Wu Y; Bai Y; Fu F; Jia X; Feng A; Liu H; Wang M
Acad Radiol; 2021 Oct; 28(10):1352-1360. PubMed ID: 32709582
[TBL] [Abstract][Full Text] [Related]
35. Prognostic aspects of lymphovascular invasion in localized gastric cancer: new insights into the radiomics and deep transfer learning from contrast-enhanced CT imaging.
Li Q; Feng QX; Qi L; Liu C; Zhang J; Yang G; Zhang YD; Liu XS
Abdom Radiol (NY); 2022 Feb; 47(2):496-507. PubMed ID: 34766197
[TBL] [Abstract][Full Text] [Related]
36. Preoperative prediction of vessel invasion in locally advanced gastric cancer based on computed tomography radiomics and machine learning.
Hu ZW; Liang P; Li ZL; Yong LL; Lu H; Wang R; Gao JB
Oncol Lett; 2023 Jul; 26(1):293. PubMed ID: 37274479
[TBL] [Abstract][Full Text] [Related]
37. Preoperative prediction of perineural invasion and lymphovascular invasion with CT radiomics in gastric cancer.
He Y; Yang M; Hou R; Ai S; Nie T; Chen J; Hu H; Guo X; Liu Y; Yuan Z
Eur J Radiol Open; 2024 Jun; 12():100550. PubMed ID: 38314183
[TBL] [Abstract][Full Text] [Related]
38. Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging.
Dai H; Lu M; Huang B; Tang M; Pang T; Liao B; Cai H; Huang M; Zhou Y; Chen X; Ding H; Feng ST
Quant Imaging Med Surg; 2021 May; 11(5):1836-1853. PubMed ID: 33936969
[TBL] [Abstract][Full Text] [Related]
39. 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]
40. Invasive ductal breast cancer: preoperative predict Ki-67 index based on radiomics of ADC maps.
Zhang Y; Zhu Y; Zhang K; Liu Y; Cui J; Tao J; Wang Y; Wang S
Radiol Med; 2020 Feb; 125(2):109-116. PubMed ID: 31696388
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]