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 *

138 related articles for article (PubMed ID: 34656249)

  • 1. Machine learning-based modified BAT score in predicting hematoma enlargement after spontaneous intracerebral hemorrhage.
    Zhou H; Zhou Z; Song Z; Li X
    J Clin Neurosci; 2021 Nov; 93():206-212. PubMed ID: 34656249
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Non-Contrast CT-Based Radiomics Score for Predicting Hematoma Enlargement in Spontaneous Intracerebral Hemorrhage.
    Li H; Xie Y; Liu H; Wang X
    Clin Neuroradiol; 2022 Jun; 32(2):517-528. PubMed ID: 34324004
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Hybrid clinical-radiomics model based on fully automatic segmentation for predicting the early expansion of spontaneous intracerebral hemorrhage: A multi-center study.
    Wang M; Liang Y; Li H; Chen J; Fu H; Wang X; Xie Y
    J Stroke Cerebrovasc Dis; 2024 Nov; 33(11):107979. PubMed ID: 39222703
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning prediction of hematoma expansion in acute intracerebral hemorrhage.
    Tanioka S; Yago T; Tanaka K; Ishida F; Kishimoto T; Tsuda K; Ikezawa M; Araki T; Miura Y; Suzuki H
    Sci Rep; 2022 Jul; 12(1):12452. PubMed ID: 35864139
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine Learning-Based Perihematomal Tissue Features to Predict Clinical Outcome after Spontaneous Intracerebral Hemorrhage.
    Qi X; Hu G; Sun H; Chen Z; Yang C
    J Stroke Cerebrovasc Dis; 2022 Jun; 31(6):106475. PubMed ID: 35417846
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Noncontrast Computed Tomography-Based Radiomics Analysis in Discriminating Early Hematoma Expansion after Spontaneous Intracerebral Hemorrhage.
    Song Z; Guo D; Tang Z; Liu H; Li X; Luo S; Yao X; Song W; Song J; Zhou Z
    Korean J Radiol; 2021 Mar; 22(3):415-424. PubMed ID: 33169546
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Radiomics features on non-contrast computed tomography predict early enlargement of spontaneous intracerebral hemorrhage.
    Li H; Xie Y; Wang X; Chen F; Sun J; Jiang X
    Clin Neurol Neurosurg; 2019 Oct; 185():105491. PubMed ID: 31470362
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of Hematoma Expansion in Intracerebral Hemorrhage in 24 Hours by Machine Learning Algorithm.
    Du C; Li Y; Yang M; Ma Q; Ge S; Ma C
    World Neurosurg; 2024 May; 185():e475-e483. PubMed ID: 38387789
    [TBL] [Abstract][Full Text] [Related]  

  • 9. BAT Score Versus Spot Sign in Predicting Intracerebral Hemorrhage Expansion.
    Yu Z; Zheng J; Xia F; Guo R; Ma L; You C; Li H
    World Neurosurg; 2019 Jun; 126():e694-e698. PubMed ID: 30844526
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Development and validation of a machine learning-based predictive model for assessing the 90-day prognostic outcome of patients with spontaneous intracerebral hemorrhage.
    Geng Z; Yang C; Zhao Z; Yan Y; Guo T; Liu C; Wu A; Wu X; Wei L; Tian Y; Hu P; Wang K
    J Transl Med; 2024 Mar; 22(1):236. PubMed ID: 38439097
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Research on predicting hematoma expansion in spontaneous intracerebral hemorrhage based on deep features of the VGG-19 network.
    Wu F; Wang P; Yang H; Wu J; Liu Y; Yang Y; Zuo Z; Wu T; Li J
    Postgrad Med J; 2024 Jul; 100(1186):592-602. PubMed ID: 38507237
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Predicting Intracerebral Hemorrhage Expansion With Noncontrast Computed Tomography: The BAT Score.
    Morotti A; Dowlatshahi D; Boulouis G; Al-Ajlan F; Demchuk AM; Aviv RI; Yu L; Schwab K; Romero JM; Gurol ME; Viswanathan A; Anderson CD; Chang Y; Greenberg SM; Qureshi AI; Rosand J; Goldstein JN;
    Stroke; 2018 May; 49(5):1163-1169. PubMed ID: 29669875
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Radiomic-based nonlinear supervised learning classifiers on non-contrast CT to predict functional prognosis in patients with spontaneous intracerebral hematoma.
    Serrano E; Moreno J; Llull L; Rodríguez A; Zwanzger C; Amaro S; Oleaga L; López-Rueda A
    Radiologia (Engl Ed); 2023; 65(6):519-530. PubMed ID: 38049251
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis.
    Liu Y; Zhao F; Niu E; Chen L
    Neuroradiology; 2024 Sep; 66(9):1603-1616. PubMed ID: 38862772
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep Learning-Based Prediction of Hematoma Expansion Using a Single Brain Computed Tomographic Slice in Patients With Spontaneous Intracerebral Hemorrhages.
    Tang Z; Zhu Y; Lu X; Wu D; Fan X; Shen J; Xiao L
    World Neurosurg; 2022 Sep; 165():e128-e136. PubMed ID: 35680084
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Noncontrast computer tomography-based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model.
    Xie H; Ma S; Wang X; Zhang X
    Eur Radiol; 2020 Jan; 30(1):87-98. PubMed ID: 31385050
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparison of Radiomic Models Based on Different Machine Learning Methods for Predicting Intracerebral Hemorrhage Expansion.
    Duan C; Liu F; Gao S; Zhao J; Niu L; Li N; Liu S; Wang G; Zhou X; Ren Y; Xu W; Liu X
    Clin Neuroradiol; 2022 Mar; 32(1):215-223. PubMed ID: 34156513
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of Ultra-Early Hematoma Growth and Common Noncontrast Computed Tomography Features in Predicting Hematoma Enlargement in Patients with Spontaneous Intracerebral Hemorrhage.
    Xiang Y; Zhang T; Li Y; Liu J; Xu H; He W; Chen Q; Yang Y
    World Neurosurg; 2020 Feb; 134():e75-e81. PubMed ID: 31648055
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using a multimodal neural network.
    Tanioka S; Aydin OU; Hilbert A; Ishida F; Tsuda K; Araki T; Nakatsuka Y; Yago T; Kishimoto T; Ikezawa M; Suzuki H; Frey D
    Sci Rep; 2024 Jul; 14(1):16465. PubMed ID: 39013990
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Establishment of a Scale for Predicting Early Hematoma Enlargement of Spontaneous Intracerebral Hemorrhage Based on Non-Contrast CT Signs.
    Li ZC; Kong XY; DU QQ; Zhang T; Wang X; Qian ZY
    Turk Neurosurg; 2023; 33(4):556-567. PubMed ID: 37309626
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.