Predicting healthcare outcomes with AI

by Neil Faulkner in Frimley, England, United Kingdom

Predicting healthcare outcomes with AI

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Flexible funding – this project will receive all pledges made by 11th August 2020 at 2:27pm

The aim of the project is to raise funds for IT equipment to help predict whether socio economic status predicts healthcare outcomes.

by Neil Faulkner in Frimley, England, United Kingdom

The global COVID-19 pandemic has created a very uncertain landscape for  millions of British small businesses, which is going to make it very challenging for businesses to survive. Together we can help them. 

The vision is to be able to predict healthcare outcomes, to reduce the expenditure that the UK currently expends on treating such diseases. The aim is to work with the community to build up the necessary data to make these predictive calculations. Diabetes in the UK for instance costs the NHS £14 billion per year. Cancer treatment in the UK costs £40 billion per year.

All data will be stored, accessed and processed in the form of a fixed format. A database of employees is a good example of structured data, where each employee has individual tables representing their name, gender, age, department, years of service, salary and so on. 

Whilst talking about datasizes, it is worth noting that Big Data sources can potentially hit the Yottabyte. Zettabytes, petabytes and yottabytes, you can be forgiven for thinking we've made this all up, but that's what Big Data Scientists and analysts have to deal with.

Intellectual property has been developed using Python to include unique libraries that are fine-tuned to handle enormous data soures. Couple these libraries with Python as a high-level language and you've got a platform that can accelerate the code enough to be able to sort through petabytes of data far quicker than any other programming language.

The computing operations support data structures in the form of lists, tuples, dictionaries and more. These operations support data frames and complex matrix operations, which greatly speed up the manipulation of huge amounts of data.

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