BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

182 related articles for article (PubMed ID: 35925956)

  • 1. A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity.
    Montaha S; Azam S; Rafid AKMRH; Islam S; Ghosh P; Jonkman M
    PLoS One; 2022; 17(8):e0269826. PubMed ID: 35925956
    [TBL] [Abstract][Full Text] [Related]  

  • 2. DePicT Melanoma Deep-CLASS: a deep convolutional neural networks approach to classify skin lesion images.
    Nasiri S; Helsper J; Jung M; Fathi M
    BMC Bioinformatics; 2020 Mar; 21(Suppl 2):84. PubMed ID: 32164530
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Melanoma classification from dermatoscopy images using knowledge distillation for highly imbalanced data.
    Adepu AK; Sahayam S; Jayaraman U; Arramraju R
    Comput Biol Med; 2023 Mar; 154():106571. PubMed ID: 36709518
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Segmentation of dermoscopy images based on deformable 3D convolution and ResU-NeXt +.
    Zhao C; Shuai R; Ma L; Liu W; Wu M
    Med Biol Eng Comput; 2021 Sep; 59(9):1815-1832. PubMed ID: 34304370
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images.
    Naeem A; Anees T; Fiza M; Naqvi RA; Lee SW
    Sensors (Basel); 2022 Jul; 22(15):. PubMed ID: 35957209
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Melanoma diagnosis using deep learning techniques on dermatoscopic images.
    Jojoa Acosta MF; Caballero Tovar LY; Garcia-Zapirain MB; Percybrooks WS
    BMC Med Imaging; 2021 Jan; 21(1):6. PubMed ID: 33407213
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.
    Ashraf H; Waris A; Ghafoor MF; Gilani SO; Niazi IK
    Sci Rep; 2022 Mar; 12(1):3948. PubMed ID: 35273282
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MNet-10: A robust shallow convolutional neural network model performing ablation study on medical images assessing the effectiveness of applying optimal data augmentation technique.
    Montaha S; Azam S; Rafid AKMRH; Hasan MZ; Karim A; Hasib KM; Patel SK; Jonkman M; Mannan ZI
    Front Med (Lausanne); 2022; 9():924979. PubMed ID: 36052321
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks.
    Yu L; Chen H; Dou Q; Qin J; Heng PA
    IEEE Trans Med Imaging; 2017 Apr; 36(4):994-1004. PubMed ID: 28026754
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Melanoma detection by analysis of clinical images using convolutional neural network.
    Nasr-Esfahani E; Samavi S; Karimi N; Soroushmehr SM; Jafari MH; Ward K; Najarian K
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():1373-1376. PubMed ID: 28268581
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks.
    Al-Masni MA; Al-Antari MA; Choi MT; Han SM; Kim TS
    Comput Methods Programs Biomed; 2018 Aug; 162():221-231. PubMed ID: 29903489
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Developing a Recognition System for Diagnosing Melanoma Skin Lesions Using Artificial Intelligence Algorithms.
    Alsaade FW; Aldhyani THH; Al-Adhaileh MH
    Comput Math Methods Med; 2021; 2021():9998379. PubMed ID: 34055044
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Classification of skin lesions using transfer learning and augmentation with Alex-net.
    Hosny KM; Kassem MA; Foaud MM
    PLoS One; 2019; 14(5):e0217293. PubMed ID: 31112591
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Skin Cancer Classification Using Deep Spiking Neural Network.
    Qasim Gilani S; Syed T; Umair M; Marques O
    J Digit Imaging; 2023 Jun; 36(3):1137-1147. PubMed ID: 36690775
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fusing fine-tuned deep features for skin lesion classification.
    Mahbod A; Schaefer G; Ellinger I; Ecker R; Pitiot A; Wang C
    Comput Med Imaging Graph; 2019 Jan; 71():19-29. PubMed ID: 30458354
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Melanoma Classification Using a Novel Deep Convolutional Neural Network with Dermoscopic Images.
    Kaur R; GholamHosseini H; Sinha R; Lindén M
    Sensors (Basel); 2022 Feb; 22(3):. PubMed ID: 35161878
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Efficient skin lesion segmentation using separable-Unet with stochastic weight averaging.
    Tang P; Liang Q; Yan X; Xiang S; Sun W; Zhang D; Coppola G
    Comput Methods Programs Biomed; 2019 Sep; 178():289-301. PubMed ID: 31416556
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.
    Baig R; Bibi M; Hamid A; Kausar S; Khalid S
    Curr Med Imaging; 2020; 16(5):513-533. PubMed ID: 32484086
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Segmentation and classification of skin lesions using hybrid deep learning method in the Internet of Medical Things.
    Akram A; Rashid J; Jaffar MA; Faheem M; Amin RU
    Skin Res Technol; 2023 Nov; 29(11):e13524. PubMed ID: 38009016
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Computer-Aided Diagnosis Algorithm for Classification of Malignant Melanoma Using Deep Neural Networks.
    Kim CI; Hwang SM; Park EB; Won CH; Lee JH
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450993
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.