AI Superior, in collaboration with an Ophthalmology Centre, has developed an advanced deep learning model to estimate the volume of fat and muscle in human eyes using CT and MRI orbit scans. By analyzing MRI scans, our model successfully segments fat and muscle tissue in each slice, allowing for accurate volume estimation and facilitating before and after volume comparisons following interventions. This groundbreaking project brings new possibilities for understanding and managing ocular health.
From Scans to Insights: Using Deep Learning to Estimate Fat and Muscle Volume of Human Eyes
Summary
Challenge
The insurance company operating in a medical/health domain was facing the challenge of pricing policies development. For them, it was important to understand risks related to a particular patient and adjust pricing policy models accordingly. In turn, the customer was expecting to experience considerable savings.
Solution by AI Superior
We built an application based on a machine learning model to predict the probabilities of a particular disease according to many input features and parameters including medical history. For that, we trained a deep learning model that was effectively dealing with intrinsic challenges such as class im-balance. Additionally, we built a validation framework to objectively compare multiple approaches and ensure that the created model was significantly outperforming others.
Outcome and Implications
The developed Data Science solution significantly outperformed the baseline models relying on statistics. The model outcome was used to optimize pricing policy to increase revenue and better manage risks.
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