Advancements in Healthcare AI technology are bound to become a norm rather than exceptions

As again the world is on the brink of being shaken by yet another Covid wave, it is time to think about why our governments are lagging in adapting to artificial intelligence even though it is proving to be successful in the healthcare sector. It was found that around 50% of US adults do not think there is any overall change in healthcare because of healthcare AI technologies, as stated in the recent survey by medical intelligence company Bluesight. This is despite the fact that there were 178 additions in AI-enabled devices to the FDA's 500+ list of approved healthcare AI technologies. Two major players in medical technology, GE Healthcare had 42 AI devices and Siemens had 29. Only these two companies accounted for around 40% of the total approved devices. What is stopping artificial intelligence from making a difference in the way healthcare is perceived?

Peter Shen, head of digital health at Siemens Healthineers North America says  AI in healthcare in use for a long time but unlike physical devices, they are not visible. Therefore personalized AI medical devices have become a priority area for Seimens. "Our strategy for AI goes beyond imaging and pattern recognition. The informed diagnostics we derive from AI allow us to design better ways to take care of patients. For us, it is about more than efficiency and more than just decision-making. We want to start to drive personalized medicine toward the patients themselves and create accessibility in medical care." Shen opines.

Advancements in medical technology mostly aim for affordable and accessible healthcare and in the process evolve into more sophisticated technologies to generate accurate results to deliver personalized care. Even though these technologies are not openly put to use in the healthcare sector, AI-enabled medical technology improvises with every new development to the great help of medical practitioners. Diagnostics has taken a never seen before leap with advanced AI technologies, particularly in Radiology and medical imaging. Currently, it constitutes around 85% of 521 devices registered with the FDA and hence the possibility of diagnostic technologies bringing in the anticipated change in the healthcare industry. A recent paper published in Nature Biomedical Engineering states how a deep learning algorithm can teach itself to identify similar features in large pathology image repositories to help diagnose and generate treatment guides for rare diseases.

A Statista report mentions, that these advancements will only grow, picking up pace with time, becoming the go-to technologies for patients interacting with them every day. Nothing proves this more than the fact that the global healthcare AI market would be worth 188 billion US dollars by 2030 and will grow at a compound growth rate of 37% from 2022 to 2030.