Artificial intelligence (AI) is all around us, and while many people worry about the possibility of robots eliminating certain jobs, there’s a whole lot of good this technology brings too, particularly when it comes to health care. Through the use of AI we could make medicines more affordable and effective and allow patients more time with their doctor’s.
Machine learning (ML) is a form of AI and its effects on the healthcare system can already be seen quite clearly. Here are just a few examples:
Various companies have been hard at it developing chatbots that can communicate with us the way another human would, making them perfect candidates to be used as therapists. One such example is a phone app called Woebot, developed by students at Stanford University. Costing between $6 and $12 a week, this app uses the power of cognitive behaviour therapy to provide counseling to those in need. It works by helping them become more aware of problematic behaviours so that they can move on to change them.
Reanalyse old drugs:
There are several new drugs developed each and every year, but very few of them prove to be effective for the purpose they’ve been made. Using AI to reanalyze these drug compounds means old drugs may become an effective form of medication, just for a different condition than it was initially designed for. Either way, it could save a lot of lives.
Big data and advanced genomics:
The power of Big Data is huge. It allows those in the medical and scientific field to benefit from the huge amounts of data stored. It enables doctors to identify unique diseases and match them to the most effective form of treatment for that patient. It’s a field that’s often referred to as precision medicine and is making a huge difference already.
Machine learning has helped to classify cancerous tumors by genetic type. This enables doctors to find the most effective treatment, specific to them. According to data released earlier this year from the American Society of Clinical Oncology, IBM’s Watson supercomputer successfully generated tumor treatment recommendations for more than 95 percent of patients tested and cut the time it takes to screen a patient by a staggering 78 percent.
Earlier diagnosis of Alzheimer’s
This neurological disease works fast, and catching the symptoms before they’ve developed too much is a challenge. Through the use of Big Data, scientists could predict who will develop the disease and start treatment early enough to delay or even prevent Alzheimer’s from progressing. This was demonstrated in a recent study where scientists achieved an 86 percent accuracy for predicting the onset of Alzheimer’s in patients.
Original article Newsweek