Medical data is an essential part of any healthcare system. This valuable information is the result of hundreds of years work by various people in the medical profession and without it, new ways to diagnose patients and new cures would never be a possibility.
However, this amount of data does not come without its downfalls. Having this much data is a lot to handle and is currently an area the healthcare industry is struggling to get to grips with. Most counties welcome the idea of having a global healthcare data center that will allow those in the medical profession to have instant access to previous research, diagnosis’, as well as new, revolutionary breakthrough techniques from all around the globe. But, the question is, “who is going to sort through all the data, standardize it, and put it into a form that is easily understood by all”? Robots, that’s who.
Artificial intelligence systems work on a whole different level to humans, and the work they can produce compared to us is quite something. Cognitive computers are self-learning systems that can find patterns in floods of unstructured data and turn it into a presentable form for everyone to be able to read. Early types of these systems that are already on the market include the AI triage service which checks patients’ symptoms against a database of over 1000 million valuations and advises them what they should do next (i.e. a home treatment or visit the doctor).
These types of systems can also be used to scan and decipher images such as CT scans, MRI scans, and X-Rays as demonstrated by a start-up company, Enlitic. The company has developed deep learning software that can use these given images to detect tiny breaks and fractures as well as early stage lung nodules and claims to be between 50 and 70 percent more accurate than alone radiologist. As well as diagnosing patients, artificial intelligence systems could also be used to prevent illnesses. This has been seen in the success of wearable devices such as Medtronic which is glucose monitor that alerts diabetes patients to any change in their blood sugar levels.
Any of these systems will save doctors valuable time and money when it comes to diagnosing and treating patients. Stratified Medical are currently working on a version of artificial intelligence that will use deep learning techniques to sort through over 20 million documents to uncover patterns between diseases and chemical compounds that scientists may not have discovered for another ten years!
With this type of technology looking to take off in the healthcare industry, the only problem left to face now is finding the people intelligent enough to be able to create these machines. With Google and Facebook often on the hunt for these people too, they are often snapped up by the big boys in the technology field rather than putting their talents to use in the healthcare sector. But, as more breakthroughs become apparent in the medical world, top class artificial intelligence engineers may well make the switch to this area as the money does rolling in.
Related Links;
– Enlitic and CH Announce Partnership Leveraging Deep Learning to Enhance Physician Care for Patients
– Machine Learning and Optimisation
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