175 related articles for article (PubMed ID: 36505817)
21. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
Gu Q; Feng Z; Liang Q; Li M; Deng J; Ma M; Wang W; Liu J; Liu P; Rong P
Eur J Radiol; 2019 Sep; 118():32-37. PubMed ID: 31439255
[TBL] [Abstract][Full Text] [Related]
22. Multiparametric Evaluation of Radiomics Features and Dual-Energy CT Iodine Maps for Discrimination and Outcome Prediction of Thymic Masses.
Mahmoudi S; Gruenewald LD; Eichler K; Althoff FC; Martin SS; Bernatz S; Booz C; Yel I; Kinzler MN; Ziegengeist NS; Torgashov K; Mohammed H; Geyer T; Scholtz JE; Hammerstingl RM; Weber C; Hardt SE; Sommer CM; Gruber-Rouh T; Leistner DM; Vogl TJ; Koch V
Acad Radiol; 2023 Dec; 30(12):3010-3021. PubMed ID: 37105804
[TBL] [Abstract][Full Text] [Related]
23. Optimizing the radiomics-machine-learning model based on non-contrast enhanced CT for the simplified risk categorization of thymic epithelial tumors: A large cohort retrospective study.
Feng XL; Wang SZ; Chen HH; Huang YX; Xin YK; Zhang T; Cheng DL; Mao L; Li XL; Liu CX; Hu YC; Wang W; Cui GB; Nan HY
Lung Cancer; 2022 Apr; 166():150-160. PubMed ID: 35287067
[TBL] [Abstract][Full Text] [Related]
24. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
[TBL] [Abstract][Full Text] [Related]
25. Application of Machine Learning and Deep EfficientNets in Distinguishing Neonatal Adrenal Hematomas From Neuroblastoma in Enhanced Computed Tomography Images.
Xie LL; Gong Y; Dong KR; Shen C; Duan B; Dong R
World J Oncol; 2024 Feb; 15(1):81-89. PubMed ID: 38274719
[TBL] [Abstract][Full Text] [Related]
26. MRI-based radiomics analysis for differentiating phyllodes tumors of the breast from fibroadenomas.
Tsuchiya M; Masui T; Terauchi K; Yamada T; Katyayama M; Ichikawa S; Noda Y; Goshima S
Eur Radiol; 2022 Jun; 32(6):4090-4100. PubMed ID: 35044510
[TBL] [Abstract][Full Text] [Related]
27. CT-Based Radiomics Signatures for Predicting the Risk Categorization of Thymic Epithelial Tumors.
Liu J; Yin P; Wang S; Liu T; Sun C; Hong N
Front Oncol; 2021; 11():628534. PubMed ID: 33718203
[TBL] [Abstract][Full Text] [Related]
28. The value of enhanced computed tomography combined with magnetic resonance imaging in the differential diagnosis of thymomas and thymic cysts before operation.
Zhang X; Zhang R; Cao Y; Wang X; Chen Y
Transl Cancer Res; 2021 Jun; 10(6):2777-2789. PubMed ID: 35116588
[TBL] [Abstract][Full Text] [Related]
29. Comparison of Radiomics-Based Machine-Learning Classifiers in Diagnosis of Glioblastoma From Primary Central Nervous System Lymphoma.
Chen C; Zheng A; Ou X; Wang J; Ma X
Front Oncol; 2020; 10():1151. PubMed ID: 33042784
[No Abstract] [Full Text] [Related]
30. Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.
Wan Q; Zhou J; Xia X; Hu J; Wang P; Peng Y; Zhang T; Sun J; Song Y; Yang G; Li X
Front Oncol; 2021; 11():683587. PubMed ID: 34868905
[TBL] [Abstract][Full Text] [Related]
31. Conventional and radiomic features to predict pathology in the preoperative assessment of anterior mediastinal masses.
Mayoral M; Pagano AM; Araujo-Filho JAB; Zheng J; Perez-Johnston R; Tan KS; Gibbs P; Fernandes Shepherd A; Rimner A; Simone II CB; Riely G; Huang J; Ginsberg MS
Lung Cancer; 2023 Apr; 178():206-212. PubMed ID: 36871345
[TBL] [Abstract][Full Text] [Related]
32. A multi-objective radiomics model for the prediction of locoregional recurrence in head and neck squamous cell cancer.
Wang K; Zhou Z; Wang R; Chen L; Zhang Q; Sher D; Wang J
Med Phys; 2020 Oct; 47(10):5392-5400. PubMed ID: 32657426
[TBL] [Abstract][Full Text] [Related]
33. Radiomics-Based Machine Learning Technology Enables Better Differentiation Between Glioblastoma and Anaplastic Oligodendroglioma.
Fan Y; Chen C; Zhao F; Tian Z; Wang J; Ma X; Xu J
Front Oncol; 2019; 9():1164. PubMed ID: 31750250
[No Abstract] [Full Text] [Related]
34. Screening of COVID-19 based on the extracted radiomics features from chest CT images.
Rezaeijo SM; Abedi-Firouzjah R; Ghorvei M; Sarnameh S
J Xray Sci Technol; 2021; 29(2):229-243. PubMed ID: 33612539
[TBL] [Abstract][Full Text] [Related]
35. Radiomics Combined with Multiple Machine Learning Algorithms in Differentiating Pancreatic Ductal Adenocarcinoma from Pancreatic Neuroendocrine Tumor: More Hands Produce a Stronger Flame.
Zhang T; Xiang Y; Wang H; Yun H; Liu Y; Wang X; Zhang H
J Clin Med; 2022 Nov; 11(22):. PubMed ID: 36431266
[TBL] [Abstract][Full Text] [Related]
36. Application of CT-Based Radiomics in Discriminating Pancreatic Cystadenomas From Pancreatic Neuroendocrine Tumors Using Machine Learning Methods.
Han X; Yang J; Luo J; Chen P; Zhang Z; Alu A; Xiao Y; Ma X
Front Oncol; 2021; 11():606677. PubMed ID: 34367940
[TBL] [Abstract][Full Text] [Related]
37. A subregion-based positron emission tomography/computed tomography (PET/CT) radiomics model for the classification of non-small cell lung cancer histopathological subtypes.
Shen H; Chen L; Liu K; Zhao K; Li J; Yu L; Ye H; Zhu W
Quant Imaging Med Surg; 2021 Jul; 11(7):2918-2932. PubMed ID: 34249623
[TBL] [Abstract][Full Text] [Related]
38. CT-based radiomics analysis of different machine learning models for differentiating benign and malignant parotid tumors.
Zheng Y; Zhou D; Liu H; Wen M
Eur Radiol; 2022 Oct; 32(10):6953-6964. PubMed ID: 35484339
[TBL] [Abstract][Full Text] [Related]
39. The CT delta-radiomics based machine learning approach in evaluating multiple primary lung adenocarcinoma.
Ma Y; Li J; Xu X; Zhang Y; Lin Y
BMC Cancer; 2022 Sep; 22(1):949. PubMed ID: 36057553
[TBL] [Abstract][Full Text] [Related]
40. Machine-learning-based contrast-enhanced computed tomography radiomic analysis for categorization of ovarian tumors.
Li J; Zhang T; Ma J; Zhang N; Zhang Z; Ye Z
Front Oncol; 2022; 12():934735. PubMed ID: 36016613
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]