At this point, the genie is out of the bottle. There is no possibility of stopping the warp-speed advances in artificial intelligence (AI) technologies, especially when it comes to human health. Contrary to what people realize, AI-driven applications are already being used across the healthcare industry and this technology has already been responsible for saving lives. It’s involved with surgery, nursing, patient diagnosis, and more.
Over the last 3 years, more hospitals and medical clinics have begun to use virtual nursing to improve the lives of patients. The benefit of AI-driven virtual nurses is that they are available 24/7, never needing a break or time away from the job. It is thought that AI-powered nurses could make up to 60 percent of all nurses in the US by 2030.
Despite the technology being in its infancy, AI-driven diagnosis is already taking place on a small scale. For example, artificial intelligence algorithms are able to problem solve on their own in order to come up with an immunotherapy solution for a specific genetic makeup. By analyzing DNA sequences and current immunotherapy medicines, AI is able to propose specific treatment solutions in order to better fight cancer.
Some of the first AI-assisted robot surgeries have taken place over the last couple of years. Many experts believe that in the coming decades, healthcare will reach a point where humans no longer carry out any surgical procedures, instead, it will be completely AI-robotics driven.
Another area where AI is already being used is in hospital and clinic-based workflow. AI is able to analyze far more data than any human ever could, allowing it to propose workflow solutions that are far more efficient than ever before. Even better is the fact that AI can now automate many administrative tasks on its own, clearing up healthcare personnel for other activities.
One of the most time-consuming healthcare tasks is image analysis. This is the practice where healthcare professionals spend hours upon hours scouring over radiology and other patient images in order to diagnose or treat a disease. Aside from the fact that the task is very time consuming, it is also prone to human error. AI systems are now analyzing medical images on their own, saving hospitals time and reducing the margin of error.