395 related articles for article (PubMed ID: 35810561)
1. Prediction of lung malignancy progression and survival with machine learning based on pre-treatment FDG-PET/CT.
Huang B; Sollee J; Luo YH; Reddy A; Zhong Z; Wu J; Mammarappallil J; Healey T; Cheng G; Azzoli C; Korogodsky D; Zhang P; Feng X; Li J; Yang L; Jiao Z; Bai HX
EBioMedicine; 2022 Aug; 82():104127. PubMed ID: 35810561
[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. Multi-lesion radiomics of PET/CT for non-invasive survival stratification and histologic tumor risk profiling in patients with lung adenocarcinoma.
Zhao M; Kluge K; Papp L; Grahovac M; Yang S; Jiang C; Krajnc D; Spielvogel CP; Ecsedi B; Haug A; Wang S; Hacker M; Zhang W; Li X
Eur Radiol; 2022 Oct; 32(10):7056-7067. PubMed ID: 35896836
[TBL] [Abstract][Full Text] [Related]
5. Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics.
Huynh BN; Groendahl AR; Tomic O; Liland KH; Knudtsen IS; Hoebers F; van Elmpt W; Malinen E; Dale E; Futsaether CM
Front Med (Lausanne); 2023; 10():1217037. PubMed ID: 37711738
[TBL] [Abstract][Full Text] [Related]
6.
Zhong H; Huang D; Wu J; Chen X; Chen Y; Huang C
BMC Med Imaging; 2023 Jun; 23(1):87. PubMed ID: 37370013
[TBL] [Abstract][Full Text] [Related]
7.
Sibille L; Seifert R; Avramovic N; Vehren T; Spottiswoode B; Zuehlsdorff S; Schäfers M
Radiology; 2020 Feb; 294(2):445-452. PubMed ID: 31821122
[TBL] [Abstract][Full Text] [Related]
8. Predicting pathological highly invasive lung cancer from preoperative [
Onozato Y; Iwata T; Uematsu Y; Shimizu D; Yamamoto T; Matsui Y; Ogawa K; Kuyama J; Sakairi Y; Kawakami E; Iizasa T; Yoshino I
Eur J Nucl Med Mol Imaging; 2023 Feb; 50(3):715-726. PubMed ID: 36385219
[TBL] [Abstract][Full Text] [Related]
9. The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [
Nakajo M; Kawaji K; Nagano H; Jinguji M; Mukai A; Kawabata H; Tani A; Hirahara D; Yamashita M; Yoshiura T
Mol Imaging Biol; 2023 Apr; 25(2):303-313. PubMed ID: 35864282
[TBL] [Abstract][Full Text] [Related]
10. Stacking Ensemble Learning-Based [
Zhao S; Wang J; Jin C; Zhang X; Xue C; Zhou R; Zhong Y; Liu Y; He X; Zhou Y; Xu C; Zhang L; Qian W; Zhang H; Zhang X; Tian M
J Nucl Med; 2023 Oct; 64(10):1603-1609. PubMed ID: 37500261
[TBL] [Abstract][Full Text] [Related]
11. Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [
Nakajo M; Jinguji M; Tani A; Kikuno H; Hirahara D; Togami S; Kobayashi H; Yoshiura T
Mol Imaging Biol; 2021 Oct; 23(5):756-765. PubMed ID: 33763816
[TBL] [Abstract][Full Text] [Related]
12. The usefulness of machine-learning-based evaluation of clinical and pretreatment
Nakajo M; Nagano H; Jinguji M; Kamimura Y; Masuda K; Takumi K; Tani A; Hirahara D; Kariya K; Yamashita M; Yoshiura T
Br J Radiol; 2023 Sep; 96(1149):20220772. PubMed ID: 37393538
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Deep Semisupervised Transfer Learning for Fully Automated Whole-Body Tumor Quantification and Prognosis of Cancer on PET/CT.
Leung KH; Rowe SP; Sadaghiani MS; Leal JP; Mena E; Choyke PL; Du Y; Pomper MG
J Nucl Med; 2024 Apr; 65(4):643-650. PubMed ID: 38423786
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.
Nair JKR; Saeed UA; McDougall CC; Sabri A; Kovacina B; Raidu BVS; Khokhar RA; Probst S; Hirsh V; Chankowsky J; Van Kempen LC; Taylor J
Can Assoc Radiol J; 2021 Feb; 72(1):109-119. PubMed ID: 32063026
[TBL] [Abstract][Full Text] [Related]
17. A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on
Wei W; Jia G; Wu Z; Wang T; Wang H; Wei K; Cheng C; Liu Z; Zuo C
Jpn J Radiol; 2023 Apr; 41(4):417-427. PubMed ID: 36409398
[TBL] [Abstract][Full Text] [Related]
18. 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]
19.
Cao L; Zhang D; Yang H; Xu W; Liu Y
World J Surg Oncol; 2023 Sep; 21(1):305. PubMed ID: 37749562
[TBL] [Abstract][Full Text] [Related]
20. Utility of pre-treatment FDG PET/CT-derived machine learning models for outcome prediction in classical Hodgkin lymphoma.
Frood R; Clark M; Burton C; Tsoumpas C; Frangi AF; Gleeson F; Patel C; Scarsbrook A
Eur Radiol; 2022 Oct; 32(10):7237-7247. PubMed ID: 36006428
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]