BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

173 related articles for article (PubMed ID: 35658345)

  • 1. [The diagnostic value of machine-learning-based model for predicting the malignancy of solid nodules in multiple pulmonary nodules].
    Zhang K; Wei ZH; Wang X; Chen KZ
    Zhonghua Wai Ke Za Zhi; 2022 Jun; 60(6):573-579. PubMed ID: 35658345
    [No Abstract]   [Full Text] [Related]  

  • 2. Establishment and validation of multiclassification prediction models for pulmonary nodules based on machine learning.
    Liu Q; Lv X; Zhou D; Yu N; Hong Y; Zeng Y
    Clin Respir J; 2024 May; 18(5):e13769. PubMed ID: 38736274
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Risk of malignancy in pulmonary nodules: A validation study of four prediction models.
    Al-Ameri A; Malhotra P; Thygesen H; Plant PK; Vaidyanathan S; Karthik S; Scarsbrook A; Callister ME
    Lung Cancer; 2015 Jul; 89(1):27-30. PubMed ID: 25864782
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Development and Validation of Machine Learning-based Model for the Prediction of Malignancy in Multiple Pulmonary Nodules: Analysis from Multicentric Cohorts.
    Chen K; Nie Y; Park S; Zhang K; Zhang Y; Liu Y; Hui B; Zhou L; Wang X; Qi Q; Li H; Kang G; Huang Y; Chen Y; Liu J; Cui J; Li M; Park IK; Kang CH; Shen H; Yang Y; Guan T; Zhang Y; Yang F; Kim YT; Wang J
    Clin Cancer Res; 2021 Apr; 27(8):2255-2265. PubMed ID: 33627492
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluation of models for predicting the probability of malignancy in patients with pulmonary nodules.
    Li Y; Hu H; Wu Z; Yan G; Wu T; Liu S; Chen W; Lu Z
    Biosci Rep; 2020 Feb; 40(2):. PubMed ID: 32068231
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A combined non-enhanced CT radiomics and clinical variable machine learning model for differentiating benign and malignant sub-centimeter pulmonary solid nodules.
    Lin RY; Zheng YN; Lv FJ; Fu BJ; Li WJ; Liang ZR; Chu ZG
    Med Phys; 2023 May; 50(5):2835-2843. PubMed ID: 36810703
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Risk assessment of malignancy in solitary pulmonary nodules in lung computed tomography: a multivariable predictive model study.
    Liu HY; Zhao XR; Chi M; Cheng XS; Wang ZQ; Xu ZW; Li YL; Yang R; Wu YJ; Zhang XJ
    Chin Med J (Engl); 2021 Jun; 134(14):1687-1694. PubMed ID: 34397595
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.
    Warkentin MT; Al-Sawaihey H; Lam S; Liu G; Diergaarde B; Yuan JM; Wilson DO; Atkar-Khattra S; Grant B; Brhane Y; Khodayari-Moez E; Murison KR; Tammemagi MC; Campbell KR; Hung RJ
    Thorax; 2024 Mar; 79(4):307-315. PubMed ID: 38195644
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparison of four models predicting the malignancy of pulmonary nodules: A single-center study of Korean adults.
    Yang B; Jhun BW; Shin SH; Jeong BH; Um SW; Zo JI; Lee HY; Sohn I; Kim H; Kwon OJ; Lee K
    PLoS One; 2018; 13(7):e0201242. PubMed ID: 30063725
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Evaluation of Prediction Models for Identifying Malignancy in Pulmonary Nodules Detected via Low-Dose Computed Tomography.
    González Maldonado S; Delorme S; Hüsing A; Motsch E; Kauczor HU; Heussel CP; Kaaks R
    JAMA Netw Open; 2020 Feb; 3(2):e1921221. PubMed ID: 32058555
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Diagnosis of Invasive Lung Adenocarcinoma Based on Chest CT Radiomic Features of Part-Solid Pulmonary Nodules: A Multicenter Study.
    Wu G; Woodruff HC; Shen J; Refaee T; Sanduleanu S; Ibrahim A; Leijenaar RTH; Wang R; Xiong J; Bian J; Wu J; Lambin P
    Radiology; 2020 Nov; 297(2):451-458. PubMed ID: 32840472
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Developing a multi-institutional nomogram for assessing lung cancer risk in patients with 5-30 mm pulmonary nodules: a retrospective analysis.
    Jiang Y; Deng T; Huang Y; Ren B; He L; Pang M; Jiang L
    PeerJ; 2023; 11():e16539. PubMed ID: 38107565
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.
    Venkadesh KV; Setio AAA; Schreuder A; Scholten ET; Chung K; W Wille MM; Saghir Z; van Ginneken B; Prokop M; Jacobs C
    Radiology; 2021 Aug; 300(2):438-447. PubMed ID: 34003056
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Establishment and validation of a clinical model for diagnosing solitary pulmonary nodules.
    Zhou L; Zhou Z; Liu F; Sun H; Zhou B; Dai L; Zhang G
    J Surg Oncol; 2022 Dec; 126(7):1316-1329. PubMed ID: 35975732
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Preoperative diagnosis of malignant pulmonary nodules in lung cancer screening with a radiomics nomogram.
    Liu A; Wang Z; Yang Y; Wang J; Dai X; Wang L; Lu Y; Xue F
    Cancer Commun (Lond); 2020 Jan; 40(1):16-24. PubMed ID: 32125097
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A simple prediction model using size measures for discrimination of invasive adenocarcinomas among incidental pulmonary subsolid nodules considered for resection.
    Kim H; Goo JM; Park CM
    Eur Radiol; 2019 Apr; 29(4):1674-1683. PubMed ID: 30255253
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Applying a CT texture analysis model trained with deep-learning reconstruction images to iterative reconstruction images in pulmonary nodule diagnosis.
    Wang Q; Xu S; Zhang G; Zhang X; Gu J; Yang S; Zeng M; Zhang Z
    J Appl Clin Med Phys; 2022 Nov; 23(11):e13759. PubMed ID: 35998185
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prior CT Improves Deep Learning for Malignancy Risk Estimation of Screening-detected Pulmonary Nodules.
    Venkadesh KV; Aleef TA; Scholten ET; Saghir Z; Silva M; Sverzellati N; Pastorino U; van Ginneken B; Prokop M; Jacobs C
    Radiology; 2023 Aug; 308(2):e223308. PubMed ID: 37526548
    [TBL] [Abstract][Full Text] [Related]  

  • 19. [Value of peripheral blood rare cell EGFR gene amplification detection in the evaluation of benign and malignant pulmonary nodules].
    Li H; Liu XQ; Yan LJ; Liu Y; Zhang JQ; Xiao YN; Li SQ
    Zhonghua Yi Xue Za Zhi; 2024 May; 104(18):1584-1589. PubMed ID: 38742345
    [No Abstract]   [Full Text] [Related]  

  • 20. A prediction model to evaluate the pretest risk of malignancy in solitary pulmonary nodules: evidence from a large Chinese southwestern population.
    Wu Z; Huang T; Zhang S; Cheng D; Li W; Chen B
    J Cancer Res Clin Oncol; 2021 Jan; 147(1):275-285. PubMed ID: 33025281
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.