The advent of commonplace artificial intelligence in healthcare is only a matter of time. Over half of health professionals feel the use of AI will be widespread within the next four years, while the market for healthcare AI is expected to reach $34 billion by 2025; a huge leap from the $1 billion of 2017.
Progress is inevitable, but both patients and physicians have their concerns. An Intel survey found that 30 percent of clinicians don’t trust AI and neither do 36 percent of patients. Conversely, other data shows patient trust of AI is on the rise, even when it’s addressing the most serious conditions.
Perhaps to reduce any stigma, the American Medical Association promotes the tech as “augmented intelligence” rather than “artificial,” while “clinical decision software” is another term used. Whatever the name, AI’s impact is slowly increasing. What are its benefits, and what will widespread adoption mean for hospitals?
“Bionic” refers to any human operations that have become enhanced through combination with machines. It’s the perfect term to describe the technological team-up to come; one that promises to provide better healthcare solutions and reduced operational costs. Some of the many positive changes that are here and likely to come to include:
Another example from the John Hopkins Hospital in 2016 bodes well for future hospitals. Predictive and data analytics allowed them to increase patient acceptance by 60 percent, dispatch critical care teams over an hour sooner, and reduce transfer delays by 70 percent, all from a central command center.
Tech giants like IBM and Google are optimistic that AI can handle tasks that are impossible for humans such as rooting out patterns in a vast amount of raw, unstructured data. Since 80 percent of healthcare data is unstructured, this means a huge volume of information can be better organized to support physicians in diagnosis and treatment. Google intends to develop AI medical tech to aid the fight against diabetes, heart disease, and Parkinson’s.
In perhaps the ultimate fusion of human and machine, Brain-Computer Interfacing is a technology that could provide a direct neurological connection between patients and AI-powered systems. These systems would allow those stricken by stroke, spinal trauma, or other speech-stealing conditions to communicate fully with their physicians.
AI seems poised to have a dramatic, positive impact on healthcare. That said, a close eye must be kept on AI development to ensure it adheres to ethical standards and those new ways of taking care of patients aren’t instituted without proper study. But it shows great promise in aiding patients, assisting physicians, and improving a hospital’s bottom line.
Medical professionals are constantly adapting to evolving variables – such as a change in status, medication, and new treatment protocols – but the sheer scale of information heading their way on a wave of Big Data means that help will be sorely needed to make sense of it all.
The ability of AI to streamline whatever it touches also applies to wireless. AI will add speed to some traditionally sluggish problem-solving areas such as judging coverage, connect time and capacity from the point of view of the end user. Poor Wi-Fi performance is contingent on several factors; whichever one is guilty will be rooted out faster thanks to AI.
Couple AI with machine learning and predictive analytics and you’ve got a way to stop problems before they even start! This will be achieved by gathering both synchronous and asynchronous data along with pre and post-connection data from every device on the network. AI will crunch those numbers and let administrators know if anything merits attention.
Effectively, we’re looking at self-regulating Wi-Fi networks. The notion of self-aware AI may spook some, but for the wireless quality, it will mean real-time analysis and action at a whole new level.
For more information, the Journal of Artificial Intelligence in Medicine and healthcare.ai are good resources to keep track of this evolving technology.
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