Ai Needs More Health Data If It's To Help Cure The World

From automated eye scans to analysing the cries of new-born babies, faster drug development to personalised medicine, artificial intelligence (AI) promises huge advances in the field of healthcare. But major challenges remain.

At the recent AI for Good Summit in Geneva, Switzerland, we were told how AI could speed up the development of new drugs, lead to personalised medicine informed by our genomes, and help diagnose diseases in countries suffering from underdeveloped health services and a chronic shortage of doctors.

But there are two main obstacles preventing access to this utopian destination.

One is that the AI being applied to the world's health problems isn't quite good enough yet. The other related issue is the lack of good quality digital data - less than 20% of the world's medical data is available in a form that AI machine learning algorithms can ingest and learn from, the WHO estimates.

As populations grow and age, more pressure is being put on doctors who are struggling to cope with the increase in administration that comes with more patients wanting to be seen more often. And in emerging economies, there simply aren't enough doctors to go around.

So many companies have been developing health advice and symptom checker apps as a way of filling the gap.

"Studies in the UK have found that 20% of people who go to the doctor don't really need to be there - the appointments are for minor ailments and injuries that could have been sorted by other means," explains Jonathon Carr-Brown, head of partnerships for Your.MD, a health information and symptom checker app.

 

As I know big data and other modern technoogies are widely used in medicine nowadays, and it is great!

 

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