131 related articles for article (PubMed ID: 31316464)
1. Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation.
Fan Y; Hua M; Mou A; Wu M; Liu X; Bao X; Wang R; Feng M
Front Endocrinol (Lausanne); 2019; 10():403. PubMed ID: 31316464
[No Abstract] [Full Text] [Related]
2. Non-invasive and real-time proliferative activity estimation based on a quantitative radiomics approach for patients with acromegaly: a multicenter study.
Fan Y; Chai Y; Li K; Fang H; Mou A; Feng S; Feng M; Wang R
J Endocrinol Invest; 2020 Jun; 43(6):755-765. PubMed ID: 31849000
[TBL] [Abstract][Full Text] [Related]
3. Machine Learning-Based Radiomics Predicts Radiotherapeutic Response in Patients With Acromegaly.
Fan Y; Jiang S; Hua M; Feng S; Feng M; Wang R
Front Endocrinol (Lausanne); 2019; 10():588. PubMed ID: 31507537
[No Abstract] [Full Text] [Related]
4. Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.
Liu Z; Zhang XY; Shi YJ; Wang L; Zhu HT; Tang Z; Wang S; Li XT; Tian J; Sun YS
Clin Cancer Res; 2017 Dec; 23(23):7253-7262. PubMed ID: 28939744
[No Abstract] [Full Text] [Related]
5. Preoperative Prediction of Meningioma Consistency
Zhai Y; Song D; Yang F; Wang Y; Jia X; Wei S; Mao W; Xue Y; Wei X
Front Oncol; 2021; 11():657288. PubMed ID: 34123812
[TBL] [Abstract][Full Text] [Related]
6. A Radiomics Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Bladder Cancer.
Wu S; Zheng J; Li Y; Yu H; Shi S; Xie W; Liu H; Su Y; Huang J; Lin T
Clin Cancer Res; 2017 Nov; 23(22):6904-6911. PubMed ID: 28874414
[No Abstract] [Full Text] [Related]
7. Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas.
Han Y; Xie Z; Zang Y; Zhang S; Gu D; Zhou M; Gevaert O; Wei J; Li C; Chen H; Du J; Liu Z; Dong D; Tian J; Zhou D
J Neurooncol; 2018 Nov; 140(2):297-306. PubMed ID: 30097822
[TBL] [Abstract][Full Text] [Related]
8. Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer.
Huang YQ; Liang CH; He L; Tian J; Liang CS; Chen X; Ma ZL; Liu ZY
J Clin Oncol; 2016 Jun; 34(18):2157-64. PubMed ID: 27138577
[TBL] [Abstract][Full Text] [Related]
9. [Preoperative evaluation of histologic grade in invasive breast cancer with T2W-MRI based radiomics signature].
Huang Y; Cheng Z; Huang X; Liang C; Liang C; Liu Z
Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2019 Mar; 44(3):285-289. PubMed ID: 30971521
[TBL] [Abstract][Full Text] [Related]
10. A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma.
Peng J; Zhang J; Zhang Q; Xu Y; Zhou J; Liu L
Diagn Interv Radiol; 2018; 24(3):121-127. PubMed ID: 29770763
[TBL] [Abstract][Full Text] [Related]
11. Using biparametric MRI radiomics signature to differentiate between benign and malignant prostate lesions.
Xu M; Fang M; Zou J; Yang S; Yu D; Zhong L; Hu C; Zang Y; Dong D; Tian J; Fang X
Eur J Radiol; 2019 May; 114():38-44. PubMed ID: 31005174
[TBL] [Abstract][Full Text] [Related]
12. Development and Validation of an MRI Radiomics-Based Signature to Predict Histological Grade in Patients with Invasive Breast Cancer.
Wang S; Wei Y; Li Z; Xu J; Zhou Y
Breast Cancer (Dove Med Press); 2022; 14():335-342. PubMed ID: 36262333
[TBL] [Abstract][Full Text] [Related]
13. Magnetic resonance imaging based radiomics signature for the preoperative discrimination of stage I-II and III-IV head and neck squamous cell carcinoma.
Ren J; Tian J; Yuan Y; Dong D; Li X; Shi Y; Tao X
Eur J Radiol; 2018 Sep; 106():1-6. PubMed ID: 30150029
[TBL] [Abstract][Full Text] [Related]
14. Multi-parametric MRI-based radiomics signature for discriminating between clinically significant and insignificant prostate cancer: Cross-validation of a machine learning method.
Min X; Li M; Dong D; Feng Z; Zhang P; Ke Z; You H; Han F; Ma H; Tian J; Wang L
Eur J Radiol; 2019 Jun; 115():16-21. PubMed ID: 31084754
[TBL] [Abstract][Full Text] [Related]
15. CT-based peritumoral radiomics signatures to predict early recurrence in hepatocellular carcinoma after curative tumor resection or ablation.
Shan QY; Hu HT; Feng ST; Peng ZP; Chen SL; Zhou Q; Li X; Xie XY; Lu MD; Wang W; Kuang M
Cancer Imaging; 2019 Feb; 19(1):11. PubMed ID: 30813956
[TBL] [Abstract][Full Text] [Related]
16. Ultrasound-based radiomics analysis in the assessment of renal fibrosis in patients with chronic kidney disease.
Chen Z; Ying MTC; Wang Y; Chen J; Wu C; Han X; Su Z
Abdom Radiol (NY); 2023 Aug; 48(8):2649-2657. PubMed ID: 37256330
[TBL] [Abstract][Full Text] [Related]
17. Development and validation of an MRI-based radiomic signature for the preoperative prediction of treatment response in patients with invasive functional pituitary adenoma.
Fan Y; Liu Z; Hou B; Li L; Liu X; Liu Z; Wang R; Lin Y; Feng F; Tian J; Feng M
Eur J Radiol; 2019 Dec; 121():108647. PubMed ID: 31561943
[TBL] [Abstract][Full Text] [Related]
18. Identification of Predominant Histopathological Growth Patterns of Colorectal Liver Metastasis by Multi-Habitat and Multi-Sequence Based Radiomics Analysis.
Han Y; Chai F; Wei J; Yue Y; Cheng J; Gu D; Zhang Y; Tong T; Sheng W; Hong N; Ye Y; Wang Y; Tian J
Front Oncol; 2020; 10():1363. PubMed ID: 32923388
[No Abstract] [Full Text] [Related]
19. The development and validation of a CT-based radiomics signature for the preoperative discrimination of stage I-II and stage III-IV colorectal cancer.
Liang C; Huang Y; He L; Chen X; Ma Z; Dong D; Tian J; Liang C; Liu Z
Oncotarget; 2016 May; 7(21):31401-12. PubMed ID: 27120787
[TBL] [Abstract][Full Text] [Related]
20. Development and assessment of machine learning algorithms for predicting remission after transsphenoidal surgery among patients with acromegaly.
Fan Y; Li Y; Li Y; Feng S; Bao X; Feng M; Wang R
Endocrine; 2020 Feb; 67(2):412-422. PubMed ID: 31673954
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]