OSIC-Pulmonary-Fibrosis-Competition

• My score = -6.92 , First position score = -6.8305

What is pulmonary fibrosis ?

Pulmonary fibrosis is a lung disease that occurs when lung tissue becomes damaged and scarred. This thickened, stiff tissue makes it more difficult for you to breathe and at a severe stage makes you become progressively more short of breath.

What we need to predict ?

We need to predict a patient’s severity of decline in lung function based on a CT scan of their lungs. Lung function is assessed based on output from a spirometer, which measures the forced vital capacity (FVC), i.e. the volume of air exhaled. The challenge is to use machine learning techniques to make a prediction with the image, metadata, and baseline FVC as input.

Evaluation metrics :-

• The evaluation metric is a modified version of Laplace Log Likelihood. Predictions are evaluated with a modified version of the Laplace Log Likelihood.

Approach :-

• Tried linear decay Resnet
• Tried EfficientNetB5
• Final predictions using Ensemble of EfficientNetB5, ElasticNet, Quantile Regression & Lasso Regression