BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

142 related articles for article (PubMed ID: 38750084)

  • 1. Prediction of treatment response after stereotactic radiosurgery of brain metastasis using deep learning and radiomics on longitudinal MRI data.
    Cho SJ; Cho W; Choi D; Sim G; Jeong SY; Baik SH; Bae YJ; Choi BS; Kim JH; Yoo S; Han JH; Kim CY; Choo J; Sunwoo L
    Sci Rep; 2024 May; 14(1):11085. PubMed ID: 38750084
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of Response to Stereotactic Radiosurgery for Brain Metastases Using Convolutional Neural Networks.
    Cha YJ; Jang WI; Kim MS; Yoo HJ; Paik EK; Jeong HK; Youn SM
    Anticancer Res; 2018 Sep; 38(9):5437-5445. PubMed ID: 30194200
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Development and validation of a radiomics-based prediction pipeline for the response to stereotactic radiosurgery therapy in brain metastases.
    Du P; Liu X; Xiang R; Lv K; Chen H; Liu W; Cao A; Chen L; Wang X; Yu T; Ding J; Li W; Li J; Li Y; Yu Z; Zhu L; Liu J; Geng D
    Eur Radiol; 2023 Dec; 33(12):8925-8935. PubMed ID: 37505244
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Computer-aided Detection of Brain Metastases in T1-weighted MRI for Stereotactic Radiosurgery Using Deep Learning Single-Shot Detectors.
    Zhou Z; Sanders JW; Johnson JM; Gule-Monroe MK; Chen MM; Briere TM; Wang Y; Son JB; Pagel MD; Li J; Ma J
    Radiology; 2020 May; 295(2):407-415. PubMed ID: 32181729
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Radiomics outperforms semantic features for prediction of response to stereotactic radiosurgery in brain metastases.
    Gutsche R; Lohmann P; Hoevels M; Ruess D; Galldiks N; Visser-Vandewalle V; Treuer H; Ruge M; Kocher M
    Radiother Oncol; 2022 Jan; 166():37-43. PubMed ID: 34801629
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predicting stereotactic radiosurgery outcomes with multi-observer qualitative appearance labelling versus MRI radiomics.
    DeVries DA; Tang T; Albweady A; Leung A; Laba J; Johnson C; Lagerwaard F; Zindler J; Hajdok G; Ward AD
    Sci Rep; 2023 Nov; 13(1):20977. PubMed ID: 38017055
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Performance sensitivity analysis of brain metastasis stereotactic radiosurgery outcome prediction using MRI radiomics.
    DeVries DA; Lagerwaard F; Zindler J; Yeung TPC; Rodrigues G; Hajdok G; Ward AD
    Sci Rep; 2022 Dec; 12(1):20975. PubMed ID: 36471160
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A priori prediction of local failure in brain metastasis after hypo-fractionated stereotactic radiotherapy using quantitative MRI and machine learning.
    Jaberipour M; Soliman H; Sahgal A; Sadeghi-Naini A
    Sci Rep; 2021 Nov; 11(1):21620. PubMed ID: 34732781
    [TBL] [Abstract][Full Text] [Related]  

  • 9. SRTRP-Net: A multi-task learning network for segmentation and prediction of stereotactic radiosurgery treatment response in brain metastases.
    Liu X; Du P; Dai Z; Yi R; Liu W; Wu H; Geng D; Liu J
    Comput Biol Med; 2024 Jun; 175():108503. PubMed ID: 38688125
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multimodality MRI-based radiomics approach to predict the posttreatment response of lung cancer brain metastases to gamma knife radiosurgery.
    Jiang Z; Wang B; Han X; Zhao P; Gao M; Zhang Y; Wei P; Lan C; Liu Y; Li D
    Eur Radiol; 2022 Apr; 32(4):2266-2276. PubMed ID: 34978579
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of treatment response in patients with brain metastasis receiving stereotactic radiosurgery based on pre-treatment multimodal MRI radiomics and clinical risk factors: A machine learning model.
    Du P; Liu X; Shen L; Wu X; Chen J; Chen L; Cao A; Geng D
    Front Oncol; 2023; 13():1114194. PubMed ID: 36994193
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Reducing false positives in deep learning-based brain metastasis detection by using both gradient-echo and spin-echo contrast-enhanced MRI: validation in a multi-center diagnostic cohort.
    Yun S; Park JE; Kim N; Park SY; Kim HS
    Eur Radiol; 2024 May; 34(5):2873-2884. PubMed ID: 37891415
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Time-delayed contrast-enhanced MRI improves detection of brain metastases and apparent treatment volumes.
    Kushnirsky M; Nguyen V; Katz JS; Steinklein J; Rosen L; Warshall C; Schulder M; Knisely JP
    J Neurosurg; 2016 Feb; 124(2):489-95. PubMed ID: 26361281
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep-learning and radiomics ensemble classifier for false positive reduction in brain metastases segmentation.
    Yang Z; Chen M; Kazemimoghadam M; Ma L; Stojadinovic S; Timmerman R; Dan T; Wardak Z; Lu W; Gu X
    Phys Med Biol; 2022 Jan; 67(2):. PubMed ID: 34952535
    [TBL] [Abstract][Full Text] [Related]  

  • 15. MRI Detection of Changes in Tissue Sodium Concentration in Brain Metastases after Stereotactic Radiosurgery: A Feasibility Study.
    A Mohamed S; Adlung A; Ruder AM; Hoesl MAU; Schad L; Groden C; Giordano FA; Neumaier-Probst E
    J Neuroimaging; 2021 Mar; 31(2):297-305. PubMed ID: 33351997
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data.
    Bousabarah K; Ruge M; Brand JS; Hoevels M; Rueß D; Borggrefe J; Große Hokamp N; Visser-Vandewalle V; Maintz D; Treuer H; Kocher M
    Radiat Oncol; 2020 Apr; 15(1):87. PubMed ID: 32312276
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach.
    Yuan J; Siakallis L; Li HB; Brandner S; Zhang J; Li C; Mancini L; Bisdas S
    BMC Med Imaging; 2024 May; 24(1):104. PubMed ID: 38702613
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Assessment of Lymphovascular Invasion in Breast Cancer Using a Combined MRI Morphological Features, Radiomics, and Deep Learning Approach Based on Dynamic Contrast-Enhanced MRI.
    Yang X; Fan X; Lin S; Zhou Y; Liu H; Wang X; Zuo Z; Zeng Y
    J Magn Reson Imaging; 2024 Jun; 59(6):2238-2249. PubMed ID: 37855421
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.
    Liu Y; Stojadinovic S; Hrycushko B; Wardak Z; Lau S; Lu W; Yan Y; Jiang SB; Zhen X; Timmerman R; Nedzi L; Gu X
    PLoS One; 2017; 12(10):e0185844. PubMed ID: 28985229
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics.
    Peng L; Parekh V; Huang P; Lin DD; Sheikh K; Baker B; Kirschbaum T; Silvestri F; Son J; Robinson A; Huang E; Ames H; Grimm J; Chen L; Shen C; Soike M; McTyre E; Redmond K; Lim M; Lee J; Jacobs MA; Kleinberg L
    Int J Radiat Oncol Biol Phys; 2018 Nov; 102(4):1236-1243. PubMed ID: 30353872
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.