An interesting trend we can see in the healthcare industry is the entry of digital technology companies like Google, Microsoft, IBM, and Apple. They bid to transform the industry with mining medical records to provide better and faster health services.
IBM Watson for instance first derives the meaning and context of the structured (such as clinical notes) and unstructured data (relevant reports) that might be critical for selecting a treatment plan. And then, combine different attributes from patient’s medical record to identify potential treatment plan for a particular patient. In short, it works like a human doctor.
And as stated by the famous American physician and co-founder of renowned Mayo Clinic, William J. Mayo — “The aim of medicine is to prevent disease and prolong life, the ideal of medicine is to eliminate the need of a physician.”
Though as of now, the focus of Artificial intelligence is more on empowering physicians rather than replacing them.
Looking at the medical AI ecosystem, we can see that much of the work is going on in Prediction and prevention, wellness, aging, rehabilitation and technological augmentation of doctors.
Out of 218 health care AI startups, 54 are involved in predictive medicine and 21 develop wellness applications (prevention). Wellness is the fastest growing segment in healthcare value chain.
With the advancements in smart machines, the healthcare industry is expected to be the fastest growing industry in data generation. According to Cisco, global machine to machine connection in healthcare is at 30% CAGR, which is the highest compared to any industry.
Tech giant IBM is trying to get hold of more and more healthcare data. It has recently partnered with Medtronic for diabetes & insulin data and acquired four healthcare companies including Explorys, Phytel, Merge healthcare and Truven Health. IBM has collected an unparalleled body of diverse health-related data, including 300 million records spanning clinical, claims, and operational data.
AI and ML are also helping in medical imaging, Drug discovery, Medication management and robotic surgery.