261 related articles for article (PubMed ID: 38429796)
21. Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.
Shiri I; Maleki H; Hajianfar G; Abdollahi H; Ashrafinia S; Hatt M; Zaidi H; Oveisi M; Rahmim A
Mol Imaging Biol; 2020 Aug; 22(4):1132-1148. PubMed ID: 32185618
[TBL] [Abstract][Full Text] [Related]
22. Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics.
Choi YS; Bae S; Chang JH; Kang SG; Kim SH; Kim J; Rim TH; Choi SH; Jain R; Lee SK
Neuro Oncol; 2021 Feb; 23(2):304-313. PubMed ID: 32706862
[TBL] [Abstract][Full Text] [Related]
23. Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.
Joo MW; Ko T; Kim MS; Lee YS; Shin SH; Chung YG; Lee HK
Clin Orthop Relat Res; 2023 Nov; 481(11):2247-2256. PubMed ID: 37615504
[TBL] [Abstract][Full Text] [Related]
24. Predicting disease recurrence in breast cancer patients using machine learning models with clinical and radiomic characteristics: a retrospective study.
Azeroual S; Ben-Bouazza FE; Naqi A; Sebihi R
J Egypt Natl Canc Inst; 2024 Jun; 36(1):20. PubMed ID: 38853190
[TBL] [Abstract][Full Text] [Related]
25. "Real-world" radiomics from multi-vendor MRI: an original retrospective study on the prediction of nodal status and disease survival in breast cancer, as an exemplar to promote discussion of the wider issues.
Doran SJ; Kumar S; Orton M; d'Arcy J; Kwaks F; O'Flynn E; Ahmed Z; Downey K; Dowsett M; Turner N; Messiou C; Koh DM
Cancer Imaging; 2021 May; 21(1):37. PubMed ID: 34016188
[TBL] [Abstract][Full Text] [Related]
26. Development and validation of ultrasound-based radiomics model to predict germline BRCA mutations in patients with breast cancer.
Deng T; Liang J; Yan C; Ni M; Xiang H; Li C; Ou J; Lin Q; Liu L; Tang G; Luo R; An X; Gao Y; Lin X
Cancer Imaging; 2024 Feb; 24(1):31. PubMed ID: 38424620
[TBL] [Abstract][Full Text] [Related]
27. Deep Learning Radiomics to Predict PTEN Mutation Status From Magnetic Resonance Imaging in Patients With Glioma.
Chen H; Lin F; Zhang J; Lv X; Zhou J; Li ZC; Chen Y
Front Oncol; 2021; 11():734433. PubMed ID: 34671557
[TBL] [Abstract][Full Text] [Related]
28. Generative adversarial network-based super-resolution of diffusion-weighted imaging: Application to tumour radiomics in breast cancer.
Fan M; Liu Z; Xu M; Wang S; Zeng T; Gao X; Li L
NMR Biomed; 2020 Aug; 33(8):e4345. PubMed ID: 32521567
[TBL] [Abstract][Full Text] [Related]
29. Evaluation of TP53/PIK3CA mutations using texture and morphology analysis on breast MRI.
Moon WK; Chen HH; Shin SU; Han W; Chang RF
Magn Reson Imaging; 2019 Nov; 63():60-69. PubMed ID: 31425802
[TBL] [Abstract][Full Text] [Related]
30. Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.
Kandemirli SG; Kocak B; Naganawa S; Ozturk K; Yip SSF; Chopra S; Rivetti L; Aldine AS; Jones K; Cayci Z; Moritani T; Sato TS
World Neurosurg; 2021 Jul; 151():e78-e85. PubMed ID: 33819703
[TBL] [Abstract][Full Text] [Related]
31. MRI Radiomics of Breast Cancer: Machine Learning-Based Prediction of Lymphovascular Invasion Status.
Kayadibi Y; Kocak B; Ucar N; Akan YN; Yildirim E; Bektas S
Acad Radiol; 2022 Jan; 29 Suppl 1():S126-S134. PubMed ID: 34876340
[TBL] [Abstract][Full Text] [Related]
32. A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer.
Hyun SH; Ahn MS; Koh YW; Lee SJ
Clin Nucl Med; 2019 Dec; 44(12):956-960. PubMed ID: 31689276
[TBL] [Abstract][Full Text] [Related]
33. Prior Clinico-Radiological Features Informed Multi-Modal MR Images Convolution Neural Network: A novel deep learning framework for prediction of lymphovascular invasion in breast cancer.
Zheng H; Jian L; Li L; Liu W; Chen W
Cancer Med; 2024 Feb; 13(3):e6932. PubMed ID: 38230837
[TBL] [Abstract][Full Text] [Related]
34. Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre- and early treatment predicts pathologic complete response.
Hussain L; Huang P; Nguyen T; Lone KJ; Ali A; Khan MS; Li H; Suh DY; Duong TQ
Biomed Eng Online; 2021 Jun; 20(1):63. PubMed ID: 34183038
[TBL] [Abstract][Full Text] [Related]
35. Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature.
Li Y; Liu X; Qian Z; Sun Z; Xu K; Wang K; Fan X; Zhang Z; Li S; Wang Y; Jiang T
Eur Radiol; 2018 Jul; 28(7):2960-2968. PubMed ID: 29404769
[TBL] [Abstract][Full Text] [Related]
36. Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.
Ha R; Chang P; Mutasa S; Karcich J; Goodman S; Blum E; Kalinsky K; Liu MZ; Jambawalikar S
J Magn Reson Imaging; 2019 Feb; 49(2):518-524. PubMed ID: 30129697
[TBL] [Abstract][Full Text] [Related]
37. Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI.
Truhn D; Schrading S; Haarburger C; Schneider H; Merhof D; Kuhl C
Radiology; 2019 Feb; 290(2):290-297. PubMed ID: 30422086
[TBL] [Abstract][Full Text] [Related]
38. MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting.
Sakai Y; Yang C; Kihira S; Tsankova N; Khan F; Hormigo A; Lai A; Cloughesy T; Nael K
Int J Mol Sci; 2020 Oct; 21(21):. PubMed ID: 33121211
[TBL] [Abstract][Full Text] [Related]
39. Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI.
Liu C; Ding J; Spuhler K; Gao Y; Serrano Sosa M; Moriarty M; Hussain S; He X; Liang C; Huang C
J Magn Reson Imaging; 2019 Jan; 49(1):131-140. PubMed ID: 30171822
[TBL] [Abstract][Full Text] [Related]
40. Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer.
Liu Q; Hu P
Biomark Res; 2023 Jan; 11(1):9. PubMed ID: 36694221
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
