Publications by authors named "Anton Cid-Mejias"
Article Synopsis
- A convolutional neural network (CNN) was developed to classify polyps as adenomatous or nonadenomatous using video data from narrow-band imaging (NBI) and NBI-near focus (NBI-NF), including sessile serrated lesions (SSLs).
- The CNN was trained on 16,832 frames from 229 polyp videos and tested with 222 polyp videos, demonstrating high sensitivity (around 89-92%) and specificity (around 88-94%) for identifying adenomas and diminutive polyps across various test sets.
- The results showed that the CNN outperformed nonexpert endoscopists in accuracy while performing comparably to experts, highlighting its potential in enhancing computer-a
Background And Objective: Nanoparticles present properties that can be applied to a wide range of fields such as biomedicine, electronics or optics. The type of properties depends on several characteristics, being some of them related with the particle structure. A proper characterization of nanoparticles is crucial since it could affect their applications.
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