
## Model description

This model is a 3D convolutional neural network model trained to predict the presence of viral pneumonia in computer tomography scans.

[Spaces link](https://huggingface.co/spaces/keras-io/3D_CNN_Pneumonia)

[Keras Example Link](https://keras.io/examples/vision/3D_image_classification/)


## Training and evaluation data

Subset of the [MosMedData: Chest CT Scans with COVID-19 Related Findings](https://www.medrxiv.org/content/10.1101/2020.05.20.20100362v1)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 100000, 'decay_rate': 0.96, 'staircase': True, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

## Model Plot

<details>
<summary>View Model Plot</summary>

![Model Image](./model.png)

</details>
{"library_name": "keras", "tags": ["3D-image-classification"]}
keras tensorboard 3D-image-classification has_space region:us
TAGS
#keras #tensorboard #3D-image-classification #has_space #region-us 


## Model description

This model is a 3D convolutional neural network model trained to predict the presence of viral pneumonia in computer tomography scans.

Spaces link

Keras Example Link


## Training and evaluation data

Subset of the MosMedData: Chest CT Scans with COVID-19 Related Findings

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 100000, 'decay_rate': 0.96, 'staircase': True, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

## Model Plot

<details>
<summary>View Model Plot</summary>

!Model Image

</details>
## Model description

This model is a 3D convolutional neural network model trained to predict the presence of viral pneumonia in computer tomography scans.

Spaces link

Keras Example Link ## Training and evaluation data

Subset of the MosMedData: Chest CT Scans with COVID-19 Related Findings ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 100000, 'decay_rate': 0.96, 'staircase': True, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32 ## Model Plot

<details>
<summary>View Model Plot</summary>

!Model Image

</details>
TAGS
#keras #tensorboard #3D-image-classification #has_space #region-us 
 ## Model description

This model is a 3D convolutional neural network model trained to predict the presence of viral pneumonia in computer tomography scans.

Spaces link

Keras Example Link ## Training and evaluation data

Subset of the MosMedData: Chest CT Scans with COVID-19 Related Findings ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 100000, 'decay_rate': 0.96, 'staircase': True, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32 ## Model Plot

<details>
<summary>View Model Plot</summary>

!Model Image

</details>
passage: TAGS
#keras #tensorboard #3D-image-classification #has_space #region-us 
## Model description

This model is a 3D convolutional neural network model trained to predict the presence of viral pneumonia in computer tomography scans.

Spaces link

Keras Example Link## Training and evaluation data

Subset of the MosMedData: Chest CT Scans with COVID-19 Related Findings## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 100000, 'decay_rate': 0.96, 'staircase': True, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32## Model Plot

<details>
<summary>View Model Plot</summary>

!Model Image

</details>