130 related articles for article (PubMed ID: 34733869)
1. Design and Assessment of Convolutional Neural Network Based Methods for Vitiligo Diagnosis.
Zhang L; Mishra S; Zhang T; Zhang Y; Zhang D; Lv Y; Lv M; Guan N; Hu XS; Chen DZ; Han X
Front Med (Lausanne); 2021; 8():754202. PubMed ID: 34733869
[No Abstract] [Full Text] [Related]
2. Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.
Tschandl P; Rosendahl C; Akay BN; Argenziano G; Blum A; Braun RP; Cabo H; Gourhant JY; Kreusch J; Lallas A; Lapins J; Marghoob A; Menzies S; Neuber NM; Paoli J; Rabinovitz HS; Rinner C; Scope A; Soyer HP; Sinz C; Thomas L; Zalaudek I; Kittler H
JAMA Dermatol; 2019 Jan; 155(1):58-65. PubMed ID: 30484822
[TBL] [Abstract][Full Text] [Related]
3. Feasibility of a generalized convolutional neural network for automated identification of vertebral compression fractures: The Manitoba Bone Mineral Density Registry.
Monchka BA; Kimelman D; Lix LM; Leslie WD
Bone; 2021 Sep; 150():116017. PubMed ID: 34020078
[TBL] [Abstract][Full Text] [Related]
4. Diagnostic performance of augmented intelligence with 2D and 3D total body photography and convolutional neural networks in a high-risk population for melanoma under real-world conditions: A new era of skin cancer screening?
Cerminara SE; Cheng P; Kostner L; Huber S; Kunz M; Maul JT; Böhm JS; Dettwiler CF; Geser A; Jakopović C; Stoffel LM; Peter JK; Levesque M; Navarini AA; Maul LV
Eur J Cancer; 2023 Sep; 190():112954. PubMed ID: 37453242
[TBL] [Abstract][Full Text] [Related]
5. Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images.
Hossain SI; de Goër de Herve J; Hassan MS; Martineau D; Petrosyan E; Corbin V; Beytout J; Lebert I; Durand J; Carravieri I; Brun-Jacob A; Frey-Klett P; Baux E; Cazorla C; Eldin C; Hansmann Y; Patrat-Delon S; Prazuck T; Raffetin A; Tattevin P; Vourc'h G; Lesens O; Nguifo EM
Comput Methods Programs Biomed; 2022 Mar; 215():106624. PubMed ID: 35051835
[TBL] [Abstract][Full Text] [Related]
6. Man against machine reloaded: performance of a market-approved convolutional neural network in classifying a broad spectrum of skin lesions in comparison with 96 dermatologists working under less artificial conditions.
Haenssle HA; Fink C; Toberer F; Winkler J; Stolz W; Deinlein T; Hofmann-Wellenhof R; Lallas A; Emmert S; Buhl T; Zutt M; Blum A; Abassi MS; Thomas L; Tromme I; Tschandl P; Enk A; Rosenberger A;
Ann Oncol; 2020 Jan; 31(1):137-143. PubMed ID: 31912788
[TBL] [Abstract][Full Text] [Related]
7. Development of a manufacturer-independent convolutional neural network for the automated identification of vertebral compression fractures in vertebral fracture assessment images using active learning.
Monchka BA; Schousboe JT; Davidson MJ; Kimelman D; Hans D; Raina P; Leslie WD
Bone; 2022 Aug; 161():116427. PubMed ID: 35489707
[TBL] [Abstract][Full Text] [Related]
8. A deep learning-based hybrid artificial intelligence model for the detection and severity assessment of vitiligo lesions.
Guo L; Yang Y; Ding H; Zheng H; Yang H; Xie J; Li Y; Lin T; Ge Y
Ann Transl Med; 2022 May; 10(10):590. PubMed ID: 35722422
[TBL] [Abstract][Full Text] [Related]
9. In-depth study of Wood's lamp examination combined with reflective confocal laser scanning microscopy for the guidance of vitiligo staging and treatment.
Hou Y; Wei Z; Jiang Q; Chen H; Chen L; Wu J
J Cosmet Dermatol; 2024 Apr; 23(4):1472-1479. PubMed ID: 38158739
[TBL] [Abstract][Full Text] [Related]
10. Computer Aided Diagnosis of Melanoma Using Deep Neural Networks and Game Theory: Application on Dermoscopic Images of Skin Lesions.
Foahom Gouabou AC; Collenne J; Monnier J; Iguernaissi R; Damoiseaux JL; Moudafi A; Merad D
Int J Mol Sci; 2022 Nov; 23(22):. PubMed ID: 36430315
[TBL] [Abstract][Full Text] [Related]
11. A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.
Mylonas A; Keall PJ; Booth JT; Shieh CC; Eade T; Poulsen PR; Nguyen DT
Med Phys; 2019 May; 46(5):2286-2297. PubMed ID: 30929254
[TBL] [Abstract][Full Text] [Related]
12. A comparative study for glioma classification using deep convolutional neural networks.
Özcan H; Emiroğlu BG; Sabuncuoğlu H; Özdoğan S; Soyer A; Saygı T
Math Biosci Eng; 2021 Jan; 18(2):1550-1572. PubMed ID: 33757198
[TBL] [Abstract][Full Text] [Related]
13. Deep learning-based automatic detection of tuberculosis disease in chest X-ray images.
Showkatian E; Salehi M; Ghaffari H; Reiazi R; Sadighi N
Pol J Radiol; 2022; 87():e118-e124. PubMed ID: 35280947
[TBL] [Abstract][Full Text] [Related]
14. Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition.
Winkler JK; Fink C; Toberer F; Enk A; Deinlein T; Hofmann-Wellenhof R; Thomas L; Lallas A; Blum A; Stolz W; Haenssle HA
JAMA Dermatol; 2019 Oct; 155(10):1135-1141. PubMed ID: 31411641
[TBL] [Abstract][Full Text] [Related]
15. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm.
Lee JH; Kim DH; Jeong SN; Choi SH
J Dent; 2018 Oct; 77():106-111. PubMed ID: 30056118
[TBL] [Abstract][Full Text] [Related]
16. Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs.
Hendrix N; Scholten E; Vernhout B; Bruijnen S; Maresch B; de Jong M; Diepstraten S; Bollen S; Schalekamp S; de Rooij M; Scholtens A; Hendrix W; Samson T; Sharon Ong LL; Postma E; van Ginneken B; Rutten M
Radiol Artif Intell; 2021 Jul; 3(4):e200260. PubMed ID: 34350413
[TBL] [Abstract][Full Text] [Related]
17. Assessment of the Robustness of Convolutional Neural Networks in Labeling Noise by Using Chest X-Ray Images From Multiple Centers.
Jang R; Kim N; Jang M; Lee KH; Lee SM; Lee KH; Noh HN; Seo JB
JMIR Med Inform; 2020 Aug; 8(8):e18089. PubMed ID: 32749222
[TBL] [Abstract][Full Text] [Related]
18. Wood's lamp for vitiligo disease stability and early recognition of initiative pigmentation after epidermal grafting.
Wang YJ; Chang CC; Cheng KL
Int Wound J; 2017 Dec; 14(6):1391-1394. PubMed ID: 28799192
[TBL] [Abstract][Full Text] [Related]
19. Visual Transformers and Convolutional Neural Networks for Disease Classification on Radiographs: A Comparison of Performance, Sample Efficiency, and Hidden Stratification.
Murphy ZR; Venkatesh K; Sulam J; Yi PH
Radiol Artif Intell; 2022 Nov; 4(6):e220012. PubMed ID: 36523640
[TBL] [Abstract][Full Text] [Related]
20. A deep learning fusion network trained with clinical and high-frequency ultrasound images in the multi-classification of skin diseases in comparison with dermatologists: a prospective and multicenter study.
Zhu AQ; Wang Q; Shi YL; Ren WW; Cao X; Ren TT; Wang J; Zhang YQ; Sun YK; Chen XW; Lai YX; Ni N; Chen YC; Hu JL; Mou LC; Zhao YJ; Liu YQ; Sun LP; Zhu XX; Xu HX; Guo LH;
EClinicalMedicine; 2024 Jan; 67():102391. PubMed ID: 38274117
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]