Cargando…
Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review
BACKGROUND: State-of-the-art classifiers based on convolutional neural networks (CNNs) were shown to classify images of skin cancer on par with dermatologists and could enable lifesaving and fast diagnoses, even outside the hospital via installation of apps on mobile devices. To our knowledge, at pr...
Autores principales: | Brinker, Titus Josef, Hekler, Achim, Utikal, Jochen Sven, Grabe, Niels, Schadendorf, Dirk, Klode, Joachim, Berking, Carola, Steeb, Theresa, Enk, Alexander H, von Kalle, Christof |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231861/ https://www.ncbi.nlm.nih.gov/pubmed/30333097 http://dx.doi.org/10.2196/11936 |
Ejemplares similares
-
Teledermatology: Comparison of Store-and-Forward Versus Live Interactive Video Conferencing
por: Brinker, Titus Josef, et al.
Publicado: (2018) -
Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions
por: Brinker, Titus J., et al.
Publicado: (2019) -
A Dermatologist's Ammunition in the War Against Smoking: A Photoaging App
por: Brinker, Titus Josef, et al.
Publicado: (2017) -
A Face-Aging App for Smoking Cessation in a Waiting Room Setting: Pilot Study in an HIV Outpatient Clinic
por: Brinker, Titus Josef, et al.
Publicado: (2018) -
Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review
por: Höhn, Julia, et al.
Publicado: (2021)