BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

148 related articles for article (PubMed ID: 38053030)

  • 21. Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM).
    R D S; A S
    Asian Pac J Cancer Prev; 2019 May; 20(5):1555-1561. PubMed ID: 31128062
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Rethinking Skin Lesion Segmentation in a Convolutional Classifier.
    Burdick J; Marques O; Weinthal J; Furht B
    J Digit Imaging; 2018 Aug; 31(4):435-440. PubMed ID: 29047032
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Melanoma Skin Cancer Detection based on Image Processing.
    Zghal NS; Derbel N
    Curr Med Imaging Rev; 2020; 16(1):50-58. PubMed ID: 31989893
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Integration of morphological preprocessing and fractal based feature extraction with recursive feature elimination for skin lesion types classification.
    Chatterjee S; Dey D; Munshi S
    Comput Methods Programs Biomed; 2019 Sep; 178():201-218. PubMed ID: 31416550
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Melanoma Classification on Dermoscopy Images Using a Neural Network Ensemble Model.
    Xie F; Fan H; Li Y; Jiang Z; Meng R; Bovik A
    IEEE Trans Med Imaging; 2017 Mar; 36(3):849-858. PubMed ID: 27913337
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Real-time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location.
    Kaur R; Albano PP; Cole JG; Hagerty J; LeAnder RW; Moss RH; Stoecker WV
    Skin Res Technol; 2015 Nov; 21(4):466-73. PubMed ID: 25809473
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Histopathological Image Classification With Color Pattern Random Binary Hashing-Based PCANet and Matrix-Form Classifier.
    Shi J; Wu J; Li Y; Zhang Q; Ying S
    IEEE J Biomed Health Inform; 2017 Sep; 21(5):1327-1337. PubMed ID: 27576270
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Progressive growing of Generative Adversarial Networks for improving data augmentation and skin cancer diagnosis.
    Pérez E; Ventura S
    Artif Intell Med; 2023 Jul; 141():102556. PubMed ID: 37295899
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Review of medical image recognition technologies to detect melanomas using neural networks.
    Efimenko M; Ignatev A; Koshechkin K
    BMC Bioinformatics; 2020 Sep; 21(Suppl 11):270. PubMed ID: 32921304
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Prediction of Skin Disease Using Ensemble Data Mining Techniques and Feature Selection Method-a Comparative Study.
    Verma AK; Pal S; Kumar S
    Appl Biochem Biotechnol; 2020 Feb; 190(2):341-359. PubMed ID: 31350666
    [TBL] [Abstract][Full Text] [Related]  

  • 31. A structured combination of ensemble classifier and filter-based feature selection to improve breast cancer diagnosis.
    Zheng D; Tang P; Lu D; Han L; Saberi S
    J Cancer Res Clin Oncol; 2023 Nov; 149(16):14519-14534. PubMed ID: 37567985
    [TBL] [Abstract][Full Text] [Related]  

  • 32. An Integrated Ensemble Network Model for Skin Abnormality Detection with Combined Textural Features.
    Sharafudeen M; S S VC
    J Digit Imaging; 2023 Aug; 36(4):1723-1738. PubMed ID: 37231287
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients.
    Aissa J; Schaarschmidt BM; Below J; Bethge OT; Böven J; Sawicki LM; Hoff NP; Kröpil P; Antoch G; Boos J
    Clin Imaging; 2018; 52():328-333. PubMed ID: 30236779
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A comparative study of deep learning architectures on melanoma detection.
    Hosseinzadeh Kassani S; Hosseinzadeh Kassani P
    Tissue Cell; 2019 Jun; 58():76-83. PubMed ID: 31133249
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Automatic segmentation and melanoma detection based on color and texture features in dermoscopic images.
    Oukil S; Kasmi R; Mokrani K; García-Zapirain B
    Skin Res Technol; 2022 Mar; 28(2):203-211. PubMed ID: 34779062
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Melanoma recognition in dermoscopy images using lesion's peripheral region information.
    Tajeddin NZ; Asl BM
    Comput Methods Programs Biomed; 2018 Sep; 163():143-153. PubMed ID: 30119849
    [TBL] [Abstract][Full Text] [Related]  

  • 37. 2-HDCNN: A two-tier hybrid dual convolution neural network feature fusion approach for diagnosing malignant melanoma.
    Nancy Jane Y; Charanya SK; Amsaprabhaa M; Jayashanker P; Nehemiah H K
    Comput Biol Med; 2023 Jan; 152():106333. PubMed ID: 36463793
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Automated multi-class classification of skin lesions through deep convolutional neural network with dermoscopic images.
    Iqbal I; Younus M; Walayat K; Kakar MU; Ma J
    Comput Med Imaging Graph; 2021 Mar; 88():101843. PubMed ID: 33445062
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Computer-aided Diagnosis of Melanoma: A Review of Existing Knowledge and Strategies.
    Maiti A; Chatterjee B; Ashour AS; Dey N
    Curr Med Imaging; 2020; 16(7):835-854. PubMed ID: 33059554
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Skin Melanoma Detection in Microscopic Images Using HMM-Based Asymmetric Analysis and Expectation Maximization.
    Rastghalam R; Danyali H; Helfroush MS; Celebi ME; Mokhtari M
    IEEE J Biomed Health Inform; 2021 Sep; 25(9):3486-3497. PubMed ID: 34003756
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.