329 related articles for article (PubMed ID: 35396665)
41. Bi-parametric magnetic resonance imaging based radiomics for the identification of benign and malignant prostate lesions: cross-vendor validation.
Ji X; Zhang J; Shi W; He D; Bao J; Wei X; Huang Y; Liu Y; Chen JC; Gao X; Tang Y; Xia W
Phys Eng Sci Med; 2021 Sep; 44(3):745-754. PubMed ID: 34075559
[TBL] [Abstract][Full Text] [Related]
42. MRI radiomics-based machine-learning classification of bone chondrosarcoma.
Gitto S; Cuocolo R; Albano D; Chianca V; Messina C; Gambino A; Ugga L; Cortese MC; Lazzara A; Ricci D; Spairani R; Zanchetta E; Luzzati A; Brunetti A; Parafioriti A; Sconfienza LM
Eur J Radiol; 2020 Jul; 128():109043. PubMed ID: 32438261
[TBL] [Abstract][Full Text] [Related]
43. A radiomics approach for automated diagnosis of ovarian neoplasm malignancy in computed tomography.
Li S; Liu J; Xiong Y; Pang P; Lei P; Zou H; Zhang M; Fan B; Luo P
Sci Rep; 2021 Apr; 11(1):8730. PubMed ID: 33888749
[TBL] [Abstract][Full Text] [Related]
44. Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.
Huang CB; Hu JS; Tan K; Zhang W; Xu TH; Yang L
BMC Geriatr; 2022 Oct; 22(1):796. PubMed ID: 36229793
[TBL] [Abstract][Full Text] [Related]
45. A combined radiomics and clinical variables model for prediction of malignancy in T2 hyperintense uterine mesenchymal tumors on MRI.
Wang T; Gong J; Li Q; Chu C; Shen W; Peng W; Gu Y; Li W
Eur Radiol; 2021 Aug; 31(8):6125-6135. PubMed ID: 33486606
[TBL] [Abstract][Full Text] [Related]
46. Malignancy risk stratification of cystic renal lesions based on a contrast-enhanced CT-based machine learning model and a clinical decision algorithm.
Dana J; Lefebvre TL; Savadjiev P; Bodard S; Gauvin S; Bhatnagar SR; Forghani R; Hélénon O; Reinhold C
Eur Radiol; 2022 Jun; 32(6):4116-4127. PubMed ID: 35066631
[TBL] [Abstract][Full Text] [Related]
47. A radiograph-based deep learning model improves radiologists' performance for classification of histological types of primary bone tumors: A multicenter study.
Xie Z; Zhao H; Song L; Ye Q; Zhong L; Li S; Zhang R; Wang M; Chen X; Lu Z; Yang W; Zhao Y
Eur J Radiol; 2024 Jul; 176():111496. PubMed ID: 38733705
[TBL] [Abstract][Full Text] [Related]
48. Using Machine Learning to Unravel the Value of Radiographic Features for the Classification of Bone Tumors.
Pan D; Liu R; Zheng B; Yuan J; Zeng H; He Z; Luo Z; Qin G; Chen W
Biomed Res Int; 2021; 2021():8811056. PubMed ID: 33791381
[TBL] [Abstract][Full Text] [Related]
49. 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]
50. Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients.
Shiri I; Sorouri M; Geramifar P; Nazari M; Abdollahi M; Salimi Y; Khosravi B; Askari D; Aghaghazvini L; Hajianfar G; Kasaeian A; Abdollahi H; Arabi H; Rahmim A; Radmard AR; Zaidi H
Comput Biol Med; 2021 May; 132():104304. PubMed ID: 33691201
[TBL] [Abstract][Full Text] [Related]
51. Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features.
Bernatz S; Ackermann J; Mandel P; Kaltenbach B; Zhdanovich Y; Harter PN; Döring C; Hammerstingl R; Bodelle B; Smith K; Bucher A; Albrecht M; Rosbach N; Basten L; Yel I; Wenzel M; Bankov K; Koch I; Chun FK; Köllermann J; Wild PJ; Vogl TJ
Eur Radiol; 2020 Dec; 30(12):6757-6769. PubMed ID: 32676784
[TBL] [Abstract][Full Text] [Related]
52. Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors.
Jan YT; Tsai PS; Huang WH; Chou LY; Huang SC; Wang JZ; Lu PH; Lin DC; Yen CS; Teng JP; Mok GSP; Shih CT; Wu TH
Insights Imaging; 2023 Apr; 14(1):68. PubMed ID: 37093321
[TBL] [Abstract][Full Text] [Related]
53. Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.
Yin P; Mao N; Zhao C; Wu J; Sun C; Chen L; Hong N
Eur Radiol; 2019 Apr; 29(4):1841-1847. PubMed ID: 30280245
[TBL] [Abstract][Full Text] [Related]
54. Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data.
He L; Li H; Dudley JA; Maloney TC; Brady SL; Somasundaram E; Trout AT; Dillman JR
AJR Am J Roentgenol; 2019 Sep; 213(3):592-601. PubMed ID: 31120779
[No Abstract] [Full Text] [Related]
55. Machine and Deep Learning Based Radiomics Models for Preoperative Prediction of Benign and Malignant Sacral Tumors.
Yin P; Mao N; Chen H; Sun C; Wang S; Liu X; Hong N
Front Oncol; 2020; 10():564725. PubMed ID: 33178593
[TBL] [Abstract][Full Text] [Related]
56. Machine learning-based CT radiomics features for the prediction of pulmonary metastasis in osteosarcoma.
Pereira HM; Leite Duarte ME; Ribeiro Damasceno I; de Oliveira Moura Santos LA; Nogueira-Barbosa MH
Br J Radiol; 2021 Aug; 94(1124):20201391. PubMed ID: 34111978
[TBL] [Abstract][Full Text] [Related]
57. Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution.
Ji Y; Li H; Edwards AV; Papaioannou J; Ma W; Liu P; Giger ML
Cancer Imaging; 2019 Sep; 19(1):64. PubMed ID: 31533838
[TBL] [Abstract][Full Text] [Related]
58. 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]
59. Distinguishing granulomas from adenocarcinomas by integrating stable and discriminating radiomic features on non-contrast computed tomography scans.
Khorrami M; Bera K; Thawani R; Rajiah P; Gupta A; Fu P; Linden P; Pennell N; Jacono F; Gilkeson RC; Velcheti V; Madabhushi A
Eur J Cancer; 2021 May; 148():146-158. PubMed ID: 33743483
[TBL] [Abstract][Full Text] [Related]
60. Applying Machine Learning Analysis Based on Proximal Femur of Abdominal Computed Tomography to Screen for Abnormal Bone Mass in Femur.
Yuan X; Liang Y; Yang H; Feng L; Sun H; Li C; Qin J
Acad Radiol; 2024 May; 31(5):2003-2010. PubMed ID: 37973518
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
