234 related articles for article (PubMed ID: 35430149)
1. Noninvasive monitoring of allograft rejection in a rat lung transplant model: Application of machine learning-based
Tian D; Shiiya H; Takahashi M; Terasaki Y; Urushiyama H; Shinozaki-Ushiku A; Yan HJ; Sato M; Nakajima J
J Heart Lung Transplant; 2022 Jun; 41(6):722-731. PubMed ID: 35430149
[TBL] [Abstract][Full Text] [Related]
2. An [
Meng N; Feng P; Yu X; Wu Y; Fu F; Li Z; Luo Y; Tan H; Yuan J; Yang Y; Wang Z; Wang M
Eur Radiol; 2024 Jan; 34(1):318-329. PubMed ID: 37530809
[TBL] [Abstract][Full Text] [Related]
3. Use of radiomics based on
Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
[TBL] [Abstract][Full Text] [Related]
4. Preoperative prediction of regional lymph node metastasis of colorectal cancer based on
He J; Wang Q; Zhang Y; Wu H; Zhou Y; Zhao S
Ann Nucl Med; 2021 May; 35(5):617-627. PubMed ID: 33738763
[TBL] [Abstract][Full Text] [Related]
5. Noninvasive Assessment of HER2 Expression Status in Gastric Cancer Using
Jiang X; Li T; Wang J; Zhang Z; Chen X; Zhang J; Zhao X
Cancer Biother Radiopharm; 2024 Apr; 39(3):169-177. PubMed ID: 38193811
[No Abstract] [Full Text] [Related]
6. Radiomics analysis for the differentiation of autoimmune pancreatitis and pancreatic ductal adenocarcinoma in
Zhang Y; Cheng C; Liu Z; Wang L; Pan G; Sun G; Chang Y; Zuo C; Yang X
Med Phys; 2019 Oct; 46(10):4520-4530. PubMed ID: 31348535
[TBL] [Abstract][Full Text] [Related]
7. CT radiomics analysis of lung cancers: Differentiation of squamous cell carcinoma from adenocarcinoma, a correlative study with FDG uptake.
Tomori Y; Yamashiro T; Tomita H; Tsubakimoto M; Ishigami K; Atsumi E; Murayama S
Eur J Radiol; 2020 Jul; 128():109032. PubMed ID: 32361604
[TBL] [Abstract][Full Text] [Related]
8. Machine learning predictive performance evaluation of conventional and fuzzy radiomics in clinical cancer imaging cohorts.
Grahovac M; Spielvogel CP; Krajnc D; Ecsedi B; Traub-Weidinger T; Rasul S; Kluge K; Zhao M; Li X; Hacker M; Haug A; Papp L
Eur J Nucl Med Mol Imaging; 2023 May; 50(6):1607-1620. PubMed ID: 36738311
[TBL] [Abstract][Full Text] [Related]
9. Molecular subtype classification of breast cancer using established radiomic signature models based on
Liu J; Bian H; Zhang Y; Gao Y; Yin G; Wang Z; Li X; Ma W; Xu W
Front Biosci (Landmark Ed); 2021 Aug; 26(9):475-484. PubMed ID: 34590460
[No Abstract] [Full Text] [Related]
10. Pre-treatment
Ahn HK; Lee H; Kim SG; Hyun SH
Clin Radiol; 2019 Jun; 74(6):467-473. PubMed ID: 30898382
[TBL] [Abstract][Full Text] [Related]
11. Maximum Standardized Uptake Value of
Niu R; Gao J; Shao X; Wang J; Jiang Z; Shi Y; Zhang F; Wang Y; Shao X
Front Oncol; 2021; 11():727094. PubMed ID: 34976790
[TBL] [Abstract][Full Text] [Related]
12. Radiomics based on
Ou X; Zhang J; Wang J; Pang F; Wang Y; Wei X; Ma X
Cancer Med; 2020 Jan; 9(2):496-506. PubMed ID: 31769230
[TBL] [Abstract][Full Text] [Related]
13. [
Noortman WA; Vriens D; de Geus-Oei LF; Slump CH; Aarntzen EH; van Berkel A; Timmers HJLM; van Velden FHP
Eur Radiol; 2022 Oct; 32(10):7227-7236. PubMed ID: 36001126
[TBL] [Abstract][Full Text] [Related]
14. Value of pre-therapy
Zhang J; Zhao X; Zhao Y; Zhang J; Zhang Z; Wang J; Wang Y; Dai M; Han J
Eur J Nucl Med Mol Imaging; 2020 May; 47(5):1137-1146. PubMed ID: 31728587
[TBL] [Abstract][Full Text] [Related]
15. Machine learning for differentiating lung squamous cell cancer from adenocarcinoma using Clinical-Metabolic characteristics and 18F-FDG PET/CT radiomics.
Zhang Y; Liu H; Chang C; Yin Y; Wang R
PLoS One; 2024; 19(4):e0300170. PubMed ID: 38568892
[TBL] [Abstract][Full Text] [Related]
16. Clinical application of
Nakajo M; Jinguji M; Ito S; Tani A; Hirahara M; Yoshiura T
Jpn J Radiol; 2024 Jan; 42(1):28-55. PubMed ID: 37526865
[TBL] [Abstract][Full Text] [Related]
17. Application of 18 F-fluorodeoxyglucose PET/CT radiomic features and machine learning to predict early recurrence of non-small cell lung cancer after curative-intent therapy.
Park SB; Kim KU; Park YW; Hwang JH; Lim CH
Nucl Med Commun; 2023 Feb; 44(2):161-168. PubMed ID: 36458424
[TBL] [Abstract][Full Text] [Related]
18. Efficient 18F-fluorodeoxyglucose positron emission tomography/computed tomography-based machine learning model for predicting epidermal growth factor receptor mutations in non-small cell lung cancer.
Ruan D; Fang J; Teng X
Q J Nucl Med Mol Imaging; 2024 Mar; 68(1):70-83. PubMed ID: 35420272
[TBL] [Abstract][Full Text] [Related]
19. Machine learning in the differentiation of follicular lymphoma from diffuse large B-cell lymphoma with radiomic [
de Jesus FM; Yin Y; Mantzorou-Kyriaki E; Kahle XU; de Haas RJ; Yakar D; Glaudemans AWJM; Noordzij W; Kwee TC; Nijland M
Eur J Nucl Med Mol Imaging; 2022 Apr; 49(5):1535-1543. PubMed ID: 34850248
[TBL] [Abstract][Full Text] [Related]
20. A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts Tumor Immune Profiles in Non-Small Cell Lung Cancer: A Retrospective Multicohort Study.
Tong H; Sun J; Fang J; Zhang M; Liu H; Xia R; Zhou W; Liu K; Chen X
Front Immunol; 2022; 13():859323. PubMed ID: 35572597
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
