In the path ahead, starting now, we will see technology not just as a welcome resource but rather as an integral part of the healthcare systems. Healthcare technology is going beyond electronic health records. It will call for greater innovation and collaboration between the healthcare provider ecosystem and third-party technology partners.
AI in healthcare will be intrinsic to almost all applications
AI is not new, in fact, it goes all the way back to Eliza, a medical chatbot developed in 1964. However, only in the last 3 years has AI and Deep Learning started to be featured in medical journals like Lancet or The New England Journal of Medicine.
A shortfall of 120,000 clinicians by 2030 pushes for the need to find ways to fill this gap through the increased use of AI applications in healthcare.
The importance of AI applications in healthcare is vital going by the projected shortfall of clinicians in the next decade in the US – a shortfall of 120,000 clinicians pushes for the need to find ways to fill this gap. Most AI applications in healthcare are based on pattern recognition, natural language processing, and predictive analytics. Taking this technology forward, AI use cases seeing increasing adoption in healthcare organizations are in robot-assisted surgery, AI based imaging is creating a new generation of radiology equipment that is developing pioneering work in tumor identification. It will also play a greater role in patient diagnostics, where predictive analytics will be able to identify infectious patterns and also pinpoint high-risk patients. We have already seen its efficacy in this pandemic, in fact this technology has had, we can say, a baptism by fire. Institutions like Mount Sinai, John Hopkins, Mayo Clinic, and the University of California pioneered the us