The 'fastai' <https://docs.fast.ai/index.html> library
simplifies training fast and accurate neural networks
using modern best practices. It is based on research
in to deep learning best practices undertaken
at 'fast.ai', including 'out of the box' support
for vision, text, tabular, audio, time series, and
collaborative filtering models.

Interface to 'fastai'

package-ubuntu-20.04-r-4.0.5#cran#fastai-2.0.7

<p>Get dicom files in 'path' recursively, only in 'folders', if specified.
</p>

get_dicom_files(path, recurse = TRUE, folders = NULL)

<table summary="R argblock">
<tr valign="top">
<td><code>path</code></td>
<td>
<p>path to files</p>
</td>
</tr>
<tr valign="top">
<td><code>recurse</code></td>
<td>
<p>recursive or not</p>
</td>
</tr>
<tr valign="top">
<td><code>folders</code></td>
<td>
<p>folder names</p>
</td>
</tr>
</table>

## Not run: 

items = get_dicom_files("siim_small/train/")



## End(Not run)

package-ubuntu-20.04-r-4.0.5#cran#fastai-2.0.7#docs#get_dicom_files

get_dicom_files

Description

Usage

Arguments

Value

Examples

fastai

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`path`	path to files
`recurse`	recursive or not
`folders`	folder names