Cargando…
Deep learning in image-based breast and cervical cancer detection: a systematic review and meta-analysis
Accurate early detection of breast and cervical cancer is vital for treatment success. Here, we conduct a meta-analysis to assess the diagnostic performance of deep learning (DL) algorithms for early breast and cervical cancer identification. Four subgroups are also investigated: cancer type (breast...
Autores principales: | Xue, Peng, Wang, Jiaxu, Qin, Dongxu, Yan, Huijiao, Qu, Yimin, Seery, Samuel, Jiang, Yu, Qiao, Youlin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847584/ https://www.ncbi.nlm.nih.gov/pubmed/35169217 http://dx.doi.org/10.1038/s41746-022-00559-z |
Ejemplares similares
-
Unassisted Clinicians Versus Deep Learning–Assisted Clinicians in Image-Based Cancer Diagnostics: Systematic Review With Meta-analysis
por: Xue, Peng, et al.
Publicado: (2023) -
Colposcopic accuracy in diagnosing squamous intraepithelial lesions: a systematic review and meta-analysis of the International Federation of Cervical Pathology and Colposcopy 2011 terminology
por: Qin, Dongxu, et al.
Publicado: (2023) -
Correction: Unassisted Clinicians Versus Deep Learning–Assisted Clinicians in Image-Based Cancer Diagnostics: Systematic Review With Meta-analysis
por: Xue, Peng, et al.
Publicado: (2023) -
Improving colposcopic accuracy for cervical precancer detection: a retrospective multicenter study in China
por: Wei, Bingrui, et al.
Publicado: (2022) -
Risk-Based Colposcopy for Cervical Precancer Detection: A Cross-Sectional Multicenter Study in China
por: Xue, Peng, et al.
Publicado: (2022)