These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

127 related articles for article (PubMed ID: 37253893)

  • 1. A Radiomics Study: Classification of Breast Lesions by Textural Features from Mammography Images.
    Letchumanan N; Wong JHD; Tan LK; Ab Mumin N; Ng WL; Chan WY; Rahmat K
    J Digit Imaging; 2023 Aug; 36(4):1533-1540. PubMed ID: 37253893
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features.
    Sakai A; Onishi Y; Matsui M; Adachi H; Teramoto A; Saito K; Fujita H
    Radiol Phys Technol; 2020 Mar; 13(1):27-36. PubMed ID: 31686300
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Combining Deep Learning and Handcrafted Radiomics for Classification of Suspicious Lesions on Contrast-enhanced Mammograms.
    Beuque MPL; Lobbes MBI; van Wijk Y; Widaatalla Y; Primakov S; Majer M; Balleyguier C; Woodruff HC; Lambin P
    Radiology; 2023 Jun; 307(5):e221843. PubMed ID: 37338353
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An Optimized Radiomics Model Based on Automated Breast Volume Scan Images to Identify Breast Lesions: Comparison of Machine Learning Methods: Comparison of Machine Learning Methods.
    Wang H; Yang X; Ma S; Zhu K; Guo S
    J Ultrasound Med; 2022 Jul; 41(7):1643-1655. PubMed ID: 34609750
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Identifying factors that may influence the classification performance of radiomics models using contrast-enhanced mammography (CEM) images.
    Sun Y; Wang S; Liu Z; You C; Li R; Mao N; Duan S; Lynn HS; Gu Y
    Cancer Imaging; 2022 May; 22(1):22. PubMed ID: 35550658
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR.
    Sun K; Jiao Z; Zhu H; Chai W; Yan X; Fu C; Cheng JZ; Yan F; Shen D
    J Transl Med; 2021 Oct; 19(1):443. PubMed ID: 34689804
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
    Wang X; Wan Q; Chen H; Li Y; Li X
    Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Diagnostic performance of perilesional radiomics analysis of contrast-enhanced mammography for the differentiation of benign and malignant breast lesions.
    Wang S; Sun Y; Li R; Mao N; Li Q; Jiang T; Chen Q; Duan S; Xie H; Gu Y
    Eur Radiol; 2022 Jan; 32(1):639-649. PubMed ID: 34189600
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Whole-tumor 3D volumetric MRI-based radiomics approach for distinguishing between benign and malignant soft tissue tumors.
    Fields BKK; Demirjian NL; Hwang DH; Varghese BA; Cen SY; Lei X; Desai B; Duddalwar V; Matcuk GR
    Eur Radiol; 2021 Nov; 31(11):8522-8535. PubMed ID: 33893534
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Added Value of Radiomics on Mammography for Breast Cancer Diagnosis: A Feasibility Study.
    Mao N; Yin P; Wang Q; Liu M; Dong J; Zhang X; Xie H; Hong N
    J Am Coll Radiol; 2019 Apr; 16(4 Pt A):485-491. PubMed ID: 30528092
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography.
    Petrillo A; Fusco R; Di Bernardo E; Petrosino T; Barretta ML; Porto A; Granata V; Di Bonito M; Fanizzi A; Massafra R; Petruzzellis N; Arezzo F; Boldrini L; La Forgia D
    Cancers (Basel); 2022 Apr; 14(9):. PubMed ID: 35565261
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.
    Lee HJ; Nguyen AT; Ki SY; Lee JE; Do LN; Park MH; Lee JS; Kim HJ; Park I; Lim HS
    Front Oncol; 2021; 11():744460. PubMed ID: 34926256
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics.
    Mao B; Ma J; Duan S; Xia Y; Tao Y; Zhang L
    Eur Radiol; 2021 Jul; 31(7):4576-4586. PubMed ID: 33447862
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Differentiation of benign from malignant solid renal lesions using CT-based radiomics and machine learning: comparison with radiologist interpretation.
    Wentland AL; Yamashita R; Kino A; Pandit P; Shen L; Brooke Jeffrey R; Rubin D; Kamaya A
    Abdom Radiol (NY); 2023 Feb; 48(2):642-648. PubMed ID: 36370180
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Incorporating the clinical and radiomics features of contrast-enhanced mammography to classify breast lesions: a retrospective study.
    Wang S; Sun Y; Mao N; Duan S; Li Q; Li R; Jiang T; Wang Z; Xie H; Gu Y
    Quant Imaging Med Surg; 2021 Oct; 11(10):4418-4430. PubMed ID: 34603996
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer.
    Petrillo A; Fusco R; Petrosino T; Vallone P; Granata V; Rubulotta MR; Pariante P; Raiano N; Scognamiglio G; Fanizzi A; Massafra R; Lafranceschina M; La Forgia D; Greco L; Ferranti FR; De Soccio V; Vidiri A; Botta F; Dominelli V; Cassano E; Sorgente E; Pecori B; Cerciello V; Boldrini L
    Radiol Med; 2024 Jun; 129(6):864-878. PubMed ID: 38755477
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A multi-stage fusion framework to classify breast lesions using deep learning and radiomics features computed from four-view mammograms.
    Jones MA; Sadeghipour N; Chen X; Islam W; Zheng B
    Med Phys; 2023 Dec; 50(12):7670-7683. PubMed ID: 37083190
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A radiomics method to classify microcalcification clusters in digital breast tomosynthesis.
    Peng Y; Wu S; Yuan G; Wu Z; Du Q; Sun H; Yang X; Chen Q; Zheng J
    Med Phys; 2020 Aug; 47(8):3435-3446. PubMed ID: 32358973
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Radiomics-based machine learning in the differentiation of benign and malignant bowel wall thickening radiomics in bowel wall thickening.
    Bülbül HM; Burakgazi G; Kesimal U; Kaba E
    Jpn J Radiol; 2024 Aug; 42(8):872-879. PubMed ID: 38536559
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.