Analysing symptoms to arrive at diagnosis conclusions

A predictive system to help doctors has been in the making for many decades now.

With the taking off of big-data analytics, systems that use symptoms and diagnose diseases can be ramped up to predict diseases. Some symptoms can be common to many ailments making diagnosis a long-drawn issue. With predictive analytics, diagnosis can be automated leading to time and cost savings for the medical practice as well as the patient. The model will bring up risk patterns in the symptoms that the doctor might miss out.

Using country-wide or worldwide data to predict epidemics

Any outbreak of a virus in a location around the world can be used with all the surrounding data to predict whether the outbreak has the potential of becoming an epidemic. Social media is also brought into the system as a reporting platform. Using current data and data from past outbreaks, a predictive analytics platform will be able to announce the next onset of a disease with high accuracy. The use of mobile phones and data on travel are all used to predict the spread of an epidemic.

Prediction of revenue by retailers

Seasonal variations in sales in different years are the norm in times of economic boom or stagnation. When retailers are able to predict demand based on economic indicators and social trends, they can have stocks available in response to a pattern that is seen on the horizon. Predictions are also very useful when retailers look to expand stores. All available relevant data can be used to guide a decision on selection of the ideal location for the next store.

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