
## Model description

We present this model in relation to previous work by [Oakden-Rayner et al.](https://arxiv.org/abs/1909.12475) and [Jiménez-Sánchez et al.](https://arxiv.org/abs/2211.04279), discussing the issue of hidden features in medical images which tend to confuse machine learning models on the task of pathology detection. 
They studied model performance on pneumothorax cases, which they find to depend on the presence of chest drains that are used for treatment of the pathology.
We developed this model as a *chest drain detector* in chest X-rays.

More details on our study as well as code and data is available [here](https://github.com/trer2547/DrainDetection_ChestXrays).

{"library_name": "keras", "tags": ["object-detection"]}
keras object-detection arxiv:1909.12475 arxiv:2211.04279 region:us
TAGS
#keras #object-detection #arxiv-1909.12475 #arxiv-2211.04279 #region-us 


## Model description

We present this model in relation to previous work by Oakden-Rayner et al. and Jiménez-Sánchez et al., discussing the issue of hidden features in medical images which tend to confuse machine learning models on the task of pathology detection. 
They studied model performance on pneumothorax cases, which they find to depend on the presence of chest drains that are used for treatment of the pathology.
We developed this model as a *chest drain detector* in chest X-rays.

More details on our study as well as code and data is available here.

## Model description

We present this model in relation to previous work by Oakden-Rayner et al. and Jiménez-Sánchez et al., discussing the issue of hidden features in medical images which tend to confuse machine learning models on the task of pathology detection. 
They studied model performance on pneumothorax cases, which they find to depend on the presence of chest drains that are used for treatment of the pathology.
We developed this model as a *chest drain detector* in chest X-rays.

More details on our study as well as code and data is available here.
TAGS
#keras #object-detection #arxiv-1909.12475 #arxiv-2211.04279 #region-us 
 ## Model description

We present this model in relation to previous work by Oakden-Rayner et al. and Jiménez-Sánchez et al., discussing the issue of hidden features in medical images which tend to confuse machine learning models on the task of pathology detection. 
They studied model performance on pneumothorax cases, which they find to depend on the presence of chest drains that are used for treatment of the pathology.
We developed this model as a *chest drain detector* in chest X-rays.

More details on our study as well as code and data is available here.
TAGS
#keras #object-detection #arxiv-1909.12475 #arxiv-2211.04279 #region-us 
## Model description

We present this model in relation to previous work by Oakden-Rayner et al. and Jiménez-Sánchez et al., discussing the issue of hidden features in medical images which tend to confuse machine learning models on the task of pathology detection. 
They studied model performance on pneumothorax cases, which they find to depend on the presence of chest drains that are used for treatment of the pathology.
We developed this model as a *chest drain detector* in chest X-rays.

More details on our study as well as code and data is available here.