388 related articles for article (PubMed ID: 31255749)
1. Assessing the effectiveness of artificial intelligence methods for melanoma: A retrospective review.
Cui X; Wei R; Gong L; Qi R; Zhao Z; Chen H; Song K; Abdulrahman AAA; Wang Y; Chen JZS; Chen S; Zhao Y; Gao X
J Am Acad Dermatol; 2019 Nov; 81(5):1176-1180. PubMed ID: 31255749
[TBL] [Abstract][Full Text] [Related]
2. Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.
Haggenmüller S; Maron RC; Hekler A; Utikal JS; Barata C; Barnhill RL; Beltraminelli H; Berking C; Betz-Stablein B; Blum A; Braun SA; Carr R; Combalia M; Fernandez-Figueras MT; Ferrara G; Fraitag S; French LE; Gellrich FF; Ghoreschi K; Goebeler M; Guitera P; Haenssle HA; Haferkamp S; Heinzerling L; Heppt MV; Hilke FJ; Hobelsberger S; Krahl D; Kutzner H; Lallas A; Liopyris K; Llamas-Velasco M; Malvehy J; Meier F; Müller CSL; Navarini AA; Navarrete-Dechent C; Perasole A; Poch G; Podlipnik S; Requena L; Rotemberg VM; Saggini A; Sangueza OP; Santonja C; Schadendorf D; Schilling B; Schlaak M; Schlager JG; Sergon M; Sondermann W; Soyer HP; Starz H; Stolz W; Vale E; Weyers W; Zink A; Krieghoff-Henning E; Kather JN; von Kalle C; Lipka DB; Fröhling S; Hauschild A; Kittler H; Brinker TJ
Eur J Cancer; 2021 Oct; 156():202-216. PubMed ID: 34509059
[TBL] [Abstract][Full Text] [Related]
3. A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task.
Brinker TJ; Hekler A; Enk AH; Klode J; Hauschild A; Berking C; Schilling B; Haferkamp S; Schadendorf D; Fröhling S; Utikal JS; von Kalle C;
Eur J Cancer; 2019 Apr; 111():148-154. PubMed ID: 30852421
[TBL] [Abstract][Full Text] [Related]
4. Deep neural networks are superior to dermatologists in melanoma image classification.
Brinker TJ; Hekler A; Enk AH; Berking C; Haferkamp S; Hauschild A; Weichenthal M; Klode J; Schadendorf D; Holland-Letz T; von Kalle C; Fröhling S; Schilling B; Utikal JS
Eur J Cancer; 2019 Sep; 119():11-17. PubMed ID: 31401469
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task.
Brinker TJ; Hekler A; Enk AH; Klode J; Hauschild A; Berking C; Schilling B; Haferkamp S; Schadendorf D; Holland-Letz T; Utikal JS; von Kalle C;
Eur J Cancer; 2019 May; 113():47-54. PubMed ID: 30981091
[TBL] [Abstract][Full Text] [Related]
7. Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition.
Winkler JK; Sies K; Fink C; Toberer F; Enk A; Abassi MS; Fuchs T; Haenssle HA
Eur J Cancer; 2021 Mar; 145():146-154. PubMed ID: 33465706
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Comprehensive analysis of clinical images contributions for melanoma classification using convolutional neural networks.
Rios-Duarte JA; Diaz-Valencia AC; Combariza G; Feles M; Peña-Silva RA
Skin Res Technol; 2024 May; 30(5):e13607. PubMed ID: 38742379
[TBL] [Abstract][Full Text] [Related]
10. Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.
Maron RC; Weichenthal M; Utikal JS; Hekler A; Berking C; Hauschild A; Enk AH; Haferkamp S; Klode J; Schadendorf D; Jansen P; Holland-Letz T; Schilling B; von Kalle C; Fröhling S; Gaiser MR; Hartmann D; Gesierich A; Kähler KC; Wehkamp U; Karoglan A; Bär C; Brinker TJ;
Eur J Cancer; 2019 Sep; 119():57-65. PubMed ID: 31419752
[TBL] [Abstract][Full Text] [Related]
11. Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge.
Combalia M; Codella N; Rotemberg V; Carrera C; Dusza S; Gutman D; Helba B; Kittler H; Kurtansky NR; Liopyris K; Marchetti MA; Podlipnik S; Puig S; Rinner C; Tschandl P; Weber J; Halpern A; Malvehy J
Lancet Digit Health; 2022 May; 4(5):e330-e339. PubMed ID: 35461690
[TBL] [Abstract][Full Text] [Related]
12. Reducing the Impact of Confounding Factors on Skin Cancer Classification via Image Segmentation: Technical Model Study.
Maron RC; Hekler A; Krieghoff-Henning E; Schmitt M; Schlager JG; Utikal JS; Brinker TJ
J Med Internet Res; 2021 Mar; 23(3):e21695. PubMed ID: 33764307
[TBL] [Abstract][Full Text] [Related]
13. Superior skin cancer classification by the combination of human and artificial intelligence.
Hekler A; Utikal JS; Enk AH; Hauschild A; Weichenthal M; Maron RC; Berking C; Haferkamp S; Klode J; Schadendorf D; Schilling B; Holland-Letz T; Izar B; von Kalle C; Fröhling S; Brinker TJ;
Eur J Cancer; 2019 Oct; 120():114-121. PubMed ID: 31518967
[TBL] [Abstract][Full Text] [Related]
14. Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.
Rajpara SM; Botello AP; Townend J; Ormerod AD
Br J Dermatol; 2009 Sep; 161(3):591-604. PubMed ID: 19302072
[TBL] [Abstract][Full Text] [Related]
15. Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.
Maron RC; Utikal JS; Hekler A; Hauschild A; Sattler E; Sondermann W; Haferkamp S; Schilling B; Heppt MV; Jansen P; Reinholz M; Franklin C; Schmitt L; Hartmann D; Krieghoff-Henning E; Schmitt M; Weichenthal M; von Kalle C; Fröhling S; Brinker TJ
J Med Internet Res; 2020 Sep; 22(9):e18091. PubMed ID: 32915161
[TBL] [Abstract][Full Text] [Related]
16. Detection of pigment network in dermoscopy images using supervised machine learning and structural analysis.
García Arroyo JL; García Zapirain B
Comput Biol Med; 2014 Jan; 44():144-57. PubMed ID: 24314859
[TBL] [Abstract][Full Text] [Related]
17. Computer-aided classification of melanocytic lesions using dermoscopic images.
Ferris LK; Harkes JA; Gilbert B; Winger DG; Golubets K; Akilov O; Satyanarayanan M
J Am Acad Dermatol; 2015 Nov; 73(5):769-76. PubMed ID: 26386631
[TBL] [Abstract][Full Text] [Related]
18. Artificial intelligence in melanoma: A systematic review.
Zhang S; Wang Y; Zheng Q; Li J; Huang J; Long X
J Cosmet Dermatol; 2022 Nov; 21(11):5993-6004. PubMed ID: 36001057
[TBL] [Abstract][Full Text] [Related]
19. Recent Advances in Melanoma Diagnosis and Prognosis Using Machine Learning Methods.
Grossarth S; Mosley D; Madden C; Ike J; Smith I; Huo Y; Wheless L
Curr Oncol Rep; 2023 Jun; 25(6):635-645. PubMed ID: 37000340
[TBL] [Abstract][Full Text] [Related]
20. Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.
Maqsood S; Damaševičius R
Neural Netw; 2023 Mar; 160():238-258. PubMed ID: 36701878
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
