Medical megafilter for the identification of potential positive patients for orphan (or rare) diseases: Gaucher, Fabry, Pompe and MPS I.

Detected needs:

- Optimize the selection of patients to be screened with specialized tests to find positive cases of carriers of any of the aforementioned diseases

- Optimization of items destined to the realization of tests for the detection of the mentioned diseases.

- Early detection of potential patients with the aforementioned diseases allows for preventive treatment and saves the health system large amounts of money needed to care for the affected population


This project allowed integrating, expanding and automating the process of detecting potential positive patients in orphan diseases (Gaucher, Fabry, Pompe and MPS I), through the synergy between practical medical knowledge, research found in academic literature and data science techniques

This project can be replicable in any Health Maintenance Organization (HMO)

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Thanks to this project it was possible to

- Improve the rate of positive diagnoses versus the screened population.

- Establish a base algorithm for the future implementation of machine learning models to strengthen the current solution for the early detection of potential patients.

- Prioritize patients with the potential to carry any of the aforementioned diseases and thus be subjected to diagnostic tests.

Technologies implemented

  • Data Science

  • HPC

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