MerSci helps payors, providers, and suppliers analyze massive amounts of clinical, claims, pharma trial, EMR, and sensor data to clarify and optimize decisions about how best to care for patients and reduce the overall cost of care.
To improve the distribution plan and optimize supply chain management, the company wants to discover the infectious diseases spreading pattern on the city level.
After several meetings with the problem owner and also other stakeholders, our data scientists visualize the spreading of the pattern for infectious diseases overtime on the country map.
Visualizing the spreading of infectious diseases showed the pattern of moving the disease from one location to another one.
Our data scientists applied Machine Learning algorithms and built a prediction model for each infectious disease on the city level for the whole country.
The prediction model provided an opportunity to deliver health-related supplies in advance before the infectious diseases hit a city.
Furthermore, the model improved the distribution management plans of the company and optimize the stock level planning for all healthcare-related institutes.
The map on the left shows how the infectious disease spread in cities. The prediction model provides the map on the right that shows how the disease will spread among the cities.
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