174 related articles for article (PubMed ID: 37067576)
1. Deep learning-assisted diagnosis of benign and malignant parotid tumors based on contrast-enhanced CT: a multicenter study.
Yu Q; Ning Y; Wang A; Li S; Gu J; Li Q; Chen X; Lv F; Zhang X; Yue Q; Peng J
Eur Radiol; 2023 Sep; 33(9):6054-6065. PubMed ID: 37067576
[TBL] [Abstract][Full Text] [Related]
2. CT-based radiomics analysis of different machine learning models for differentiating benign and malignant parotid tumors.
Zheng Y; Zhou D; Liu H; Wen M
Eur Radiol; 2022 Oct; 32(10):6953-6964. PubMed ID: 35484339
[TBL] [Abstract][Full Text] [Related]
3. Development and Validation of Contrast-Enhanced CT-Based Deep Transfer Learning and Combined Clinical-Radiomics Model to Discriminate Thymomas and Thymic Cysts: A Multicenter Study.
Yang Y; Cheng J; Peng Z; Yi L; Lin Z; He A; Jin M; Cui C; Liu Y; Zhong Q; Zuo M
Acad Radiol; 2024 Apr; 31(4):1615-1628. PubMed ID: 37949702
[TBL] [Abstract][Full Text] [Related]
4. Machine learning-based radiomics for histological classification of parotid tumors using morphological MRI: a comparative study.
He Z; Mao Y; Lu S; Tan L; Xiao J; Tan P; Zhang H; Li G; Yan H; Tan J; Huang D; Qiu Y; Zhang X; Wang X; Liu Y
Eur Radiol; 2022 Dec; 32(12):8099-8110. PubMed ID: 35748897
[TBL] [Abstract][Full Text] [Related]
5. Deep learning-assisted diagnosis of parotid gland tumors by using contrast-enhanced CT imaging.
Shen XM; Mao L; Yang ZY; Chai ZK; Sun TG; Xu Y; Sun ZJ
Oral Dis; 2023 Nov; 29(8):3325-3336. PubMed ID: 36520552
[TBL] [Abstract][Full Text] [Related]
6. Differentiation of benign and malignant parotid gland tumors based on the fusion of radiomics and deep learning features on ultrasound images.
Wang Y; Gao J; Yin Z; Wen Y; Sun M; Han R
Front Oncol; 2024; 14():1384105. PubMed ID: 38803533
[TBL] [Abstract][Full Text] [Related]
7. Multiphasic CT-Based Radiomics Analysis for the Differentiation of Benign and Malignant Parotid Tumors.
Yu Q; Wang A; Gu J; Li Q; Ning Y; Peng J; Lv F; Zhang X
Front Oncol; 2022; 12():913898. PubMed ID: 35847942
[TBL] [Abstract][Full Text] [Related]
8. Integrating intratumoral and peritumoral radiomics with deep transfer learning for DCE-MRI breast lesion differentiation: A multicenter study comparing performance with radiologists.
Yu T; Yu R; Liu M; Wang X; Zhang J; Zheng Y; Lv F
Eur J Radiol; 2024 Jun; 177():111556. PubMed ID: 38875748
[TBL] [Abstract][Full Text] [Related]
9. Enhanced CT-based texture analysis and radiomics score for differentiation of pleomorphic adenoma, basal cell adenoma, and Warthin tumor of the parotid gland.
Chen F; Ge Y; Li S; Liu M; Wu J; Liu Y
Dentomaxillofac Radiol; 2023 Jan; 52(2):20220009. PubMed ID: 36367128
[TBL] [Abstract][Full Text] [Related]
10. Development and validation of CT-based radiomics nomogram for the classification of benign parotid gland tumors.
Zheng M; Chen Q; Ge Y; Yang L; Tian Y; Liu C; Wang P; Deng K
Med Phys; 2023 Feb; 50(2):947-957. PubMed ID: 36273307
[TBL] [Abstract][Full Text] [Related]
11. Using deep learning to distinguish malignant from benign parotid tumors on plain computed tomography images.
Hu Z; Wang B; Pan X; Cao D; Gao A; Yang X; Chen Y; Lin Z
Front Oncol; 2022; 12():919088. PubMed ID: 35978811
[TBL] [Abstract][Full Text] [Related]
12. A deep learning model integrating mammography and clinical factors facilitates the malignancy prediction of BI-RADS 4 microcalcifications in breast cancer screening.
Liu H; Chen Y; Zhang Y; Wang L; Luo R; Wu H; Wu C; Zhang H; Tan W; Yin H; Wang D
Eur Radiol; 2021 Aug; 31(8):5902-5912. PubMed ID: 33496829
[TBL] [Abstract][Full Text] [Related]
13. Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors.
Jan YT; Tsai PS; Huang WH; Chou LY; Huang SC; Wang JZ; Lu PH; Lin DC; Yen CS; Teng JP; Mok GSP; Shih CT; Wu TH
Insights Imaging; 2023 Apr; 14(1):68. PubMed ID: 37093321
[TBL] [Abstract][Full Text] [Related]
14. A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study.
Cui Y; Zhang J; Li Z; Wei K; Lei Y; Ren J; Wu L; Shi Z; Meng X; Yang X; Gao X
EClinicalMedicine; 2022 Apr; 46():101348. PubMed ID: 35340629
[TBL] [Abstract][Full Text] [Related]
15. A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma.
Xiang F; Meng QT; Deng JJ; Wang J; Liang XY; Liu XY; Yan S
Hepatobiliary Pancreat Dis Int; 2024 Aug; 23(4):376-384. PubMed ID: 37080813
[TBL] [Abstract][Full Text] [Related]
16. A Combined Model Integrating Radiomics and Deep Learning Based on Contrast-Enhanced CT for Preoperative Staging of Laryngeal Carcinoma.
Chen X; Yu Q; Peng J; He Z; Li Q; Ning Y; Gu J; Lv F; Jiang H; Xie K
Acad Radiol; 2023 Dec; 30(12):3022-3031. PubMed ID: 37777428
[TBL] [Abstract][Full Text] [Related]
17. A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors.
Liu R; Pan D; Xu Y; Zeng H; He Z; Lin J; Zeng W; Wu Z; Luo Z; Qin G; Chen W
Eur Radiol; 2022 Feb; 32(2):1371-1383. PubMed ID: 34432121
[TBL] [Abstract][Full Text] [Related]
18. A CT-based radiomics nomogram for differentiation of lympho-associated benign and malignant lesions of the parotid gland.
Zheng YM; Xu WJ; Hao DP; Liu XJ; Gao CP; Tang GZ; Li J; Wang HX; Dong C
Eur Radiol; 2021 May; 31(5):2886-2895. PubMed ID: 33123791
[TBL] [Abstract][Full Text] [Related]
19. Differentiating Benign from Malignant Renal Tumors Using T2- and Diffusion-Weighted Images: A Comparison of Deep Learning and Radiomics Models Versus Assessment from Radiologists.
Xu Q; Zhu Q; Liu H; Chang L; Duan S; Dou W; Li S; Ye J
J Magn Reson Imaging; 2022 Apr; 55(4):1251-1259. PubMed ID: 34462986
[TBL] [Abstract][Full Text] [Related]
20. The Diagnostic Value of Ultrasound-Based Deep Learning in Differentiating Parotid Gland Tumors.
Wang Y; Xie W; Huang S; Feng M; Ke X; Zhong Z; Tang L
J Oncol; 2022; 2022():8192999. PubMed ID: 35602298
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
