BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

150 related articles for article (PubMed ID: 38684143)

  • 1. Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).
    Yang R; Zhang Y; Li W; Li Q; Liu X; Zhang F; Liang Z; Huang J; Li X; Tao L; Guo X
    Biomed Phys Eng Express; 2024 May; 10(4):. PubMed ID: 38684143
    [No Abstract]   [Full Text] [Related]  

  • 2. 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]  

  • 3. Development and clinical application of deep learning model for lung nodules screening on CT images.
    Cui S; Ming S; Lin Y; Chen F; Shen Q; Li H; Chen G; Gong X; Wang H
    Sci Rep; 2020 Aug; 10(1):13657. PubMed ID: 32788705
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance.
    Schwyzer M; Martini K; Benz DC; Burger IA; Ferraro DA; Kudura K; Treyer V; von Schulthess GK; Kaufmann PA; Huellner MW; Messerli M
    Eur Radiol; 2020 Apr; 30(4):2031-2040. PubMed ID: 31822970
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.
    Liang CH; Liu YC; Wu MT; Garcia-Castro F; Alberich-Bayarri A; Wu FZ
    Clin Radiol; 2020 Jan; 75(1):38-45. PubMed ID: 31521323
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.
    Yang X; Chu XP; Huang S; Xiao Y; Li D; Su X; Qi YF; Qiu ZB; Wang Y; Tang WF; Wu YL; Zhu Q; Liang H; Zhong WZ
    Eur Radiol; 2024 Mar; 34(3):2048-2061. PubMed ID: 37658883
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.
    Huang W; Xue Y; Wu Y
    PLoS One; 2019; 14(7):e0219369. PubMed ID: 31299053
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Robust explanation supervision for false positive reduction in pulmonary nodule detection.
    Zhao Q; Chang CW; Yang X; Zhao L
    Med Phys; 2024 Mar; 51(3):1687-1701. PubMed ID: 38224306
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines.
    van Riel SJ; Ciompi F; Jacobs C; Winkler Wille MM; Scholten ET; Naqibullah M; Lam S; Prokop M; Schaefer-Prokop C; van Ginneken B
    Eur Radiol; 2017 Oct; 27(10):4019-4029. PubMed ID: 28293773
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Automated Pulmonary Nodule Classification in Computed Tomography Images Using a Deep Convolutional Neural Network Trained by Generative Adversarial Networks.
    Onishi Y; Teramoto A; Tsujimoto M; Tsukamoto T; Saito K; Toyama H; Imaizumi K; Fujita H
    Biomed Res Int; 2019; 2019():6051939. PubMed ID: 30719445
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Assessment of indeterminate pulmonary nodules detected in lung cancer screening: Diagnostic accuracy of FDG PET/CT.
    Garcia-Velloso MJ; Bastarrika G; de-Torres JP; Lozano MD; Sanchez-Salcedo P; Sancho L; Nuñez-Cordoba JM; Campo A; Alcaide AB; Torre W; Richter JA; Zulueta JJ
    Lung Cancer; 2016 Jul; 97():81-6. PubMed ID: 27237032
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.
    Feng B; Chen X; Chen Y; Lu S; Liu K; Li K; Liu Z; Hao Y; Li Z; Zhu Z; Yao N; Liang G; Zhang J; Long W; Liu X
    Eur Radiol; 2020 Dec; 30(12):6497-6507. PubMed ID: 32594210
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules.
    Massion PP; Antic S; Ather S; Arteta C; Brabec J; Chen H; Declerck J; Dufek D; Hickes W; Kadir T; Kunst J; Landman BA; Munden RF; Novotny P; Peschl H; Pickup LC; Santos C; Smith GT; Talwar A; Gleeson F
    Am J Respir Crit Care Med; 2020 Jul; 202(2):241-249. PubMed ID: 32326730
    [No Abstract]   [Full Text] [Related]  

  • 17. Attention pyramid pooling network for artificial diagnosis on pulmonary nodules.
    Wang H; Zhu H; Ding L; Yang K
    PLoS One; 2024; 19(5):e0302641. PubMed ID: 38753596
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predicting Malignancy Risk of Screen-Detected Lung Nodules-Mean Diameter or Volume.
    Tammemagi M; Ritchie AJ; Atkar-Khattra S; Dougherty B; Sanghera C; Mayo JR; Yuan R; Manos D; McWilliams AM; Schmidt H; Gingras M; Pasian S; Stewart L; Tsai S; Seely JM; Burrowes P; Bhatia R; Haider EA; Boylan C; Jacobs C; van Ginneken B; Tsao MS; Lam S;
    J Thorac Oncol; 2019 Feb; 14(2):203-211. PubMed ID: 30368011
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Differentiation of Benign from Malignant Pulmonary Nodules by Using a Convolutional Neural Network to Determine Volume Change at Chest CT.
    Ohno Y; Aoyagi K; Yaguchi A; Seki S; Ueno Y; Kishida Y; Takenaka D; Yoshikawa T
    Radiology; 2020 Aug; 296(2):432-443. PubMed ID: 32452736
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population.
    Murchison JT; Ritchie G; Senyszak D; Nijwening JH; van Veenendaal G; Wakkie J; van Beek EJR
    PLoS One; 2022; 17(5):e0266799. PubMed ID: 35511758
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.