Ai In The Medical Field

By Author: Charlotte
Total Articles: 11
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AI is definitely an emerging technology. Especially now that the likes of Google and Amazon have bought in their AI bots allowing you to ask what the weather is, what is on your calendar or remind you to walk the dog. However there are far more serious uses for AI and the medical field is leading the technology march.

Imagine you had a leading surgeon, you would want them to teach as many up and coming surgeons as possible. AI makes this possible as the top surgeon's skills can be programmed into an AI programme that can be used for training purposes. How about practicing these skills learnt? Again AI combined with Virtual Reality will enable a training student to practice operating in real time, with AI feeding back suggestions as well as running scenarios good and bad.

Artificial intelligence helps pharma companies find patients for clinical trials. While AI can be used to make sense of clinical trials data, another use of artificial intelligence in the pharmaceutical industry is to find the patients to take them. App Developers Canada, On Demand App Development Company ...
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However AI is also helping out on the more mundane areas of the health service. From simple situations like managing appointments to much more complex support environments such as research information, AI is supporting, improving and assisting the medical field.

So how does AI improve such, what could be on the face of it, reasonably simple solutions? To start we need to investigate the power of AI.

At its simplest terms AI is defined as software that thinks and makes decisions in a similar manner to the human brain. When you consider that the mind does not even understand how it works, that could on the facial skin of it be a brave definition. When you also consider that AI has been around and in use for at least 20 years but it is only in the last few years it has begun to be very useful, it becomes a challenging definition. Despite what many science fiction books and movies state, AI is not set to take over the world, but rather become a supporting environment.

So we get to the definition that AI can work in the same way as the human brain, react to situations and produce life like scenarios and responses. Also if you think of famous brands Siri and Alexa, it can produce realistic answers to a large number of questions that are answered in various manners. However anyone who has despaired of getting Siri to answer the question you have actually asked, there are still limitations.

So what is in the future for medical uses of AI? Well to clarify first, there are companies such as John Snow Labs, the 2018 AI solution provider winner, that are at the cutting edge of AI research and that future is rapidly progressing and coming closer.

Bringing life changing drugs to market has always been a long drawn out and costly process. AI can not only support the processes involved but also assist working way through the analysis produced, making real life, human like decisions in order to shorten searches and decisions. Now obviously there needs to be a final human being decision, but decision paths are shorter.

So how is machine learning becoming so useful?
At its most basic machine learning is skilled at operating millions of algorithms in a short time frame and providing the resulting conclusions to the human operator for their review and decision. The beauty is that this speed of testing algorithms is vastly quicker than the mind can undertake.

The second major difference to normal powerful data processing software is, that AI or machine learning software can use these algorithms to learn from the patterns and then create its own logic. Within medical research these algorithms are tested many an incredible number of times until consistent results are produced. These email address details are then turned over to the medical professional to make the individual decision based on the AI research.

When you look at such areas as medical research where there are thousands of different possible outcomes and even more variables, coupled with a healthy clutch of things that can go wrong, it is easy to see why machine learning programmes are so welcomed by the medical field.

When looking at medical treatment, it is the myriad of factors that can wrong where machine learning comes to the fore. Often combined with Virtual Reality (VR) practical operations can be set up, enabling the surgeon to apply their skills without fear of injuring or even killing the patient. The surgeon can practice the heart transplant numerous times with the AI providing multiple scenarios predicated on the surgeon's activities until they are confident enough to undertake the operation on a real live person.

Using similar scenarios, treatment research can be tried and tested until a suitable new treatment has been found, with the AI suggesting differing methods, outcomes and problems as the surgeons work.

I am a writer and marketing manager by profession.