BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

300 related articles for article (PubMed ID: 34441324)

  • 1. Machine Learning and Deep Learning Methods for Skin Lesion Classification and Diagnosis: A Systematic Review.
    Kassem MA; Hosny KM; Damaševičius R; Eltoukhy MM
    Diagnostics (Basel); 2021 Jul; 11(8):. PubMed ID: 34441324
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Skin Lesion Classification and Detection Using Machine Learning Techniques: A Systematic Review.
    Debelee TG
    Diagnostics (Basel); 2023 Oct; 13(19):. PubMed ID: 37835889
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated detection of nonmelanoma skin cancer using digital images: a systematic review.
    Marka A; Carter JB; Toto E; Hassanpour S
    BMC Med Imaging; 2019 Feb; 19(1):21. PubMed ID: 30819133
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A survey, review, and future trends of skin lesion segmentation and classification.
    Hasan MK; Ahamad MA; Yap CH; Yang G
    Comput Biol Med; 2023 Mar; 155():106624. PubMed ID: 36774890
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Computer-aided diagnosis of liver lesions using CT images: A systematic review.
    Nayantara PV; Kamath S; Manjunath KN; Rajagopal KV
    Comput Biol Med; 2020 Dec; 127():104035. PubMed ID: 33099219
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Recent Advancements and Perspectives in the Diagnosis of Skin Diseases Using Machine Learning and Deep Learning: A Review.
    Zhang J; Zhong F; He K; Ji M; Li S; Li C
    Diagnostics (Basel); 2023 Nov; 13(23):. PubMed ID: 38066747
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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]  

  • 10. Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.
    Al-Antari MA; Al-Masni MA; Kim TS
    Adv Exp Med Biol; 2020; 1213():59-72. PubMed ID: 32030663
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Blood cell image segmentation and classification: a systematic review.
    Shahzad M; Ali F; Shirazi SH; Rasheed A; Ahmad A; Shah B; Kwak D
    PeerJ Comput Sci; 2024; 10():e1813. PubMed ID: 38435563
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey.
    Asiri N; Hussain M; Al Adel F; Alzaidi N
    Artif Intell Med; 2019 Aug; 99():101701. PubMed ID: 31606116
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification.
    Al-Antari MA; Al-Masni MA; Choi MT; Han SM; Kim TS
    Int J Med Inform; 2018 Sep; 117():44-54. PubMed ID: 30032964
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Transfer learning using a multi-scale and multi-network ensemble for skin lesion classification.
    Mahbod A; Schaefer G; Wang C; Dorffner G; Ecker R; Ellinger I
    Comput Methods Programs Biomed; 2020 Sep; 193():105475. PubMed ID: 32268255
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Skin lesion classification with ensembles of deep convolutional neural networks.
    Harangi B
    J Biomed Inform; 2018 Oct; 86():25-32. PubMed ID: 30103029
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
    Woldaregay AZ; Årsand E; Walderhaug S; Albers D; Mamykina L; Botsis T; Hartvigsen G
    Artif Intell Med; 2019 Jul; 98():109-134. PubMed ID: 31383477
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Review of Computer-Aided Expert Systems for Breast Cancer Diagnosis.
    Liew XY; Hameed N; Clos J
    Cancers (Basel); 2021 Jun; 13(11):. PubMed ID: 34199444
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.
    Yassin NIR; Omran S; El Houby EMF; Allam H
    Comput Methods Programs Biomed; 2018 Mar; 156():25-45. PubMed ID: 29428074
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Skin Lesion Analysis and Cancer Detection Based on Machine/Deep Learning Techniques: A Comprehensive Survey.
    Zafar M; Sharif MI; Sharif MI; Kadry S; Bukhari SAC; Rauf HT
    Life (Basel); 2023 Jan; 13(1):. PubMed ID: 36676093
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.