764 related articles for article (PubMed ID: 31306724)
1. Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.
Marchetti MA; Liopyris K; Dusza SW; Codella NCF; Gutman DA; Helba B; Kalloo A; Halpern AC;
J Am Acad Dermatol; 2020 Mar; 82(3):622-627. PubMed ID: 31306724
[TBL] [Abstract][Full Text] [Related]
2. Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images.
Marchetti MA; Codella NCF; Dusza SW; Gutman DA; Helba B; Kalloo A; Mishra N; Carrera C; Celebi ME; DeFazio JL; Jaimes N; Marghoob AA; Quigley E; Scope A; Yélamos O; Halpern AC;
J Am Acad Dermatol; 2018 Feb; 78(2):270-277.e1. PubMed ID: 28969863
[TBL] [Abstract][Full Text] [Related]
3. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.
Haenssle HA; Fink C; Schneiderbauer R; Toberer F; Buhl T; Blum A; Kalloo A; Hassen ABH; Thomas L; Enk A; Uhlmann L; ; Alt C; Arenbergerova M; Bakos R; Baltzer A; Bertlich I; Blum A; Bokor-Billmann T; Bowling J; Braghiroli N; Braun R; Buder-Bakhaya K; Buhl T; Cabo H; Cabrijan L; Cevic N; Classen A; Deltgen D; Fink C; Georgieva I; Hakim-Meibodi LE; Hanner S; Hartmann F; Hartmann J; Haus G; Hoxha E; Karls R; Koga H; Kreusch J; Lallas A; Majenka P; Marghoob A; Massone C; Mekokishvili L; Mestel D; Meyer V; Neuberger A; Nielsen K; Oliviero M; Pampena R; Paoli J; Pawlik E; Rao B; Rendon A; Russo T; Sadek A; Samhaber K; Schneiderbauer R; Schweizer A; Toberer F; Trennheuser L; Vlahova L; Wald A; Winkler J; Wölbing P; Zalaudek I
Ann Oncol; 2018 Aug; 29(8):1836-1842. PubMed ID: 29846502
[TBL] [Abstract][Full Text] [Related]
4. A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.
Tognetti L; Bonechi S; Andreini P; Bianchini M; Scarselli F; Cevenini G; Moscarella E; Farnetani F; Longo C; Lallas A; Carrera C; Puig S; Tiodorovic D; Perrot JL; Pellacani G; Argenziano G; Cinotti E; Cataldo G; Balistreri A; Mecocci A; Gori M; Rubegni P; Cartocci A
J Dermatol Sci; 2021 Feb; 101(2):115-122. PubMed ID: 33358096
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults.
Dinnes J; Deeks JJ; Chuchu N; Ferrante di Ruffano L; Matin RN; Thomson DR; Wong KY; Aldridge RB; Abbott R; Fawzy M; Bayliss SE; Grainge MJ; Takwoingi Y; Davenport C; Godfrey K; Walter FM; Williams HC;
Cochrane Database Syst Rev; 2018 Dec; 12(12):CD011902. PubMed ID: 30521682
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. Differentiation of melanoma from benign mimics using the relative-color method.
LeAnder R; Chindam P; Das M; Umbaugh SE
Skin Res Technol; 2010 Aug; 16(3):297-304. PubMed ID: 20636998
[TBL] [Abstract][Full Text] [Related]
11. AI outperformed every dermatologist in dermoscopic melanoma diagnosis, using an optimized deep-CNN architecture with custom mini-batch logic and loss function.
Pham TC; Luong CM; Hoang VD; Doucet A
Sci Rep; 2021 Sep; 11(1):17485. PubMed ID: 34471174
[TBL] [Abstract][Full Text] [Related]
12. Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders.
Han SS; Park I; Eun Chang S; Lim W; Kim MS; Park GH; Chae JB; Huh CH; Na JI
J Invest Dermatol; 2020 Sep; 140(9):1753-1761. PubMed ID: 32243882
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Density-based parallel skin lesion border detection with webCL.
Lemon J; Kockara S; Halic T; Mete M
BMC Bioinformatics; 2015; 16 Suppl 13(Suppl 13):S5. PubMed ID: 26423836
[TBL] [Abstract][Full Text] [Related]
15. Deep learning-based, computer-aided classifier developed with dermoscopic images shows comparable performance to 164 dermatologists in cutaneous disease diagnosis in the Chinese population.
Wang SQ; Zhang XY; Liu J; Tao C; Zhu CY; Shu C; Xu T; Jin HZ
Chin Med J (Engl); 2020 Sep; 133(17):2027-2036. PubMed ID: 32826613
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. The performance of SolarScan: an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma.
Menzies SW; Bischof L; Talbot H; Gutenev A; Avramidis M; Wong L; Lo SK; Mackellar G; Skladnev V; McCarthy W; Kelly J; Cranney B; Lye P; Rabinovitz H; Oliviero M; Blum A; Varol A; De'Ambrosis B; McCleod R; Koga H; Grin C; Braun R; Johr R
Arch Dermatol; 2005 Nov; 141(11):1388-96. PubMed ID: 16301386
[TBL] [Abstract][Full Text] [Related]
18. The dermoscopic inverse approach significantly improves the accuracy of human readers for lentigo maligna diagnosis.
Lallas A; Lallas K; Tschandl P; Kittler H; Apalla Z; Longo C; Argenziano G
J Am Acad Dermatol; 2021 Feb; 84(2):381-389. PubMed ID: 32592885
[TBL] [Abstract][Full Text] [Related]
19. Dermatologist-level classification of skin cancer with deep neural networks.
Esteva A; Kuprel B; Novoa RA; Ko J; Swetter SM; Blau HM; Thrun S
Nature; 2017 Feb; 542(7639):115-118. PubMed ID: 28117445
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
