BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

239 related articles for article (PubMed ID: 37370013)

  • 1.
    Zhong H; Huang D; Wu J; Chen X; Chen Y; Huang C
    BMC Med Imaging; 2023 Jun; 23(1):87. PubMed ID: 37370013
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Overall Survival Prognostic Modelling of Non-small Cell Lung Cancer Patients Using Positron Emission Tomography/Computed Tomography Harmonised Radiomics Features: The Quest for the Optimal Machine Learning Algorithm.
    Amini M; Hajianfar G; Hadadi Avval A; Nazari M; Deevband MR; Oveisi M; Shiri I; Zaidi H
    Clin Oncol (R Coll Radiol); 2022 Feb; 34(2):114-127. PubMed ID: 34872823
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of lung malignancy progression and survival with machine learning based on pre-treatment FDG-PET/CT.
    Huang B; Sollee J; Luo YH; Reddy A; Zhong Z; Wu J; Mammarappallil J; Healey T; Cheng G; Azzoli C; Korogodsky D; Zhang P; Feng X; Li J; Yang L; Jiao Z; Bai HX
    EBioMedicine; 2022 Aug; 82():104127. PubMed ID: 35810561
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Multimodality radiomics analysis based on [
    Xu H; Lv W; Zhang H; Yuan Q; Wang Q; Wu Y; Lu L
    Eur Radiol; 2023 Oct; 33(10):6677-6688. PubMed ID: 37060444
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Radiomics signature from [
    Jiang C; Huang X; Li A; Teng Y; Ding C; Chen J; Xu J; Zhou Z
    Eur Radiol; 2022 Aug; 32(8):5730-5741. PubMed ID: 35298676
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A machine learning approach using
    Qi WX; Li S; Xiao J; Li H; Chen J; Zhao S
    Front Immunol; 2024; 15():1351750. PubMed ID: 38352868
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Stacking Ensemble Learning-Based [
    Zhao S; Wang J; Jin C; Zhang X; Xue C; Zhou R; Zhong Y; Liu Y; He X; Zhou Y; Xu C; Zhang L; Qian W; Zhang H; Zhang X; Tian M
    J Nucl Med; 2023 Oct; 64(10):1603-1609. PubMed ID: 37500261
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [
    Nakajo M; Jinguji M; Tani A; Kikuno H; Hirahara D; Togami S; Kobayashi H; Yoshiura T
    Mol Imaging Biol; 2021 Oct; 23(5):756-765. PubMed ID: 33763816
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine learning based evaluation of clinical and pretreatment
    Nakajo M; Jinguji M; Tani A; Yano E; Hoo CK; Hirahara D; Togami S; Kobayashi H; Yoshiura T
    Abdom Radiol (NY); 2022 Feb; 47(2):838-847. PubMed ID: 34821963
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Construction and validation of an
    Dong X; Wang R; Ying X; Xu J; Yan J; Xu P; Peng Y; Chen B
    Hematology; 2024 Dec; 29(1):2329029. PubMed ID: 38488443
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Use of radiomics based on
    Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
    Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning based on clinico-biological features integrated
    Ren C; Zhang J; Qi M; Zhang J; Zhang Y; Song S; Sun Y; Cheng J
    Eur J Nucl Med Mol Imaging; 2021 May; 48(5):1538-1549. PubMed ID: 33057772
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The usefulness of machine-learning-based evaluation of clinical and pretreatment
    Nakajo M; Nagano H; Jinguji M; Kamimura Y; Masuda K; Takumi K; Tani A; Hirahara D; Kariya K; Yamashita M; Yoshiura T
    Br J Radiol; 2023 Sep; 96(1149):20220772. PubMed ID: 37393538
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Radiomics analysis for the differentiation of autoimmune pancreatitis and pancreatic ductal adenocarcinoma in
    Zhang Y; Cheng C; Liu Z; Wang L; Pan G; Sun G; Chang Y; Zuo C; Yang X
    Med Phys; 2019 Oct; 46(10):4520-4530. PubMed ID: 31348535
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Clinical application of
    Nakajo M; Jinguji M; Ito S; Tani A; Hirahara M; Yoshiura T
    Jpn J Radiol; 2024 Jan; 42(1):28-55. PubMed ID: 37526865
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Random survival forest to predict transplant-eligible newly diagnosed multiple myeloma outcome including FDG-PET radiomics: a combined analysis of two independent prospective European trials.
    Jamet B; Morvan L; Nanni C; Michaud AV; Bailly C; Chauvie S; Moreau P; Touzeau C; Zamagni E; Bodet-Milin C; Kraeber-Bodéré F; Mateus D; Carlier T
    Eur J Nucl Med Mol Imaging; 2021 Apr; 48(4):1005-1015. PubMed ID: 33006656
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [
    Nakajo M; Kawaji K; Nagano H; Jinguji M; Mukai A; Kawabata H; Tani A; Hirahara D; Yamashita M; Yoshiura T
    Mol Imaging Biol; 2023 Apr; 25(2):303-313. PubMed ID: 35864282
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Leveraging RSF and PET images for prognosis of multiple myeloma at diagnosis.
    Morvan L; Carlier T; Jamet B; Bailly C; Bodet-Milin C; Moreau P; Kraeber-Bodéré F; Mateus D
    Int J Comput Assist Radiol Surg; 2020 Jan; 15(1):129-139. PubMed ID: 31256359
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prognostic Value of
    Carlier T; Frécon G; Mateus D; Rizkallah M; Kraeber-Bodéré F; Kanoun S; Blanc-Durand P; Itti E; Le Gouill S; Casasnovas RO; Bodet-Milin C; Bailly C
    J Nucl Med; 2024 Jan; 65(1):156-162. PubMed ID: 37945379
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Optimal
    Zuo Y; Liu Q; Li N; Li P; Zhang J; Song S
    Front Oncol; 2023; 13():1173355. PubMed ID: 37223682
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.