There is a constant buzz about how disruptive technologies are creating new markets and pushing the old ones out of business. Previously, companies had time to think, evaluate, and justify decisions to deploy new strategies and technologies. But, in this era of smart connected products, manufacturers must be agile and incorporate the technology that customers are looking for in their next-generation products and create a digital thread – that connects critical information to track a product and its digital assets from concept to market. All industrial sectors are feeling the heat to adopt new technologies – and the healthcare sector is no exception.
There is a huge market for artificial intelligence AI in the healthcare sector and many companies, such as Google, Apple, Dell, HewlettPackard, Siemens, Bentley Systems etc. have already cashed in on this. Hospitals, insurance companies, and industries with ties to healthcare have all been impacted. For example, just a few years ago portable ECG machines were in great demand; but now it has become redundant as the smartwatch and iPhones can perform the same function. AI has provided the ability to attach artificial limbs and implant devices to help people walk again; and these are great inventions.
Useful AI Applications
As technology usage has increased in all areas, so too has it changed the ways in which we seek medical care - medical records are digitized, appointments are scheduled online, patients can check in to health centers or clinics using their phones etc. I believe that AI in the healthcare sector is particularly useful in the following applications:
- Compiling, analyzing, and managing medical records
- Selecting appropriate treatment plans
- Online/digital consultation
- Medication advice and management
- Laboratory information management systems (LIMS)
- Health monitoring through health trackers
The potential for increased AI usage in medicine is not just in a reduction of manual tasks and increasing efficiency and patient care - it also presents the opportunity to move towards more “precision medicine.” Robots already assist in spinal surgery, with models such as Renaissance allowing surgeons to place screws in spines with 99 percent accuracy (9 percent higher than conventional methods). A few other AI systems:
WOEBOT: The name says it all – a robot to listen to your woes! This chatbot app checks in daily to help users monitor their mental health.
WATSON: Created by IBM to aid diagnosis and management plans for cancer patients. The Icon Group in Australia announced a planned deal with IBM in June 2017.
DA VINCI: Used for a variety of surgical procedures in which surgeon’s hand movements are robotically recreated.
PARO: This robotic seal has been used for over 15 years in hospitals and aged-care homes worldwide to reduce stress and improve socialization.
STAR: A surgical robot that can independently suture soft tissue (with surgeon supervision). Currently, it’s only used at the Children’s National Medical Center in Washington.
What Will the Future of AI in Healthcare be Like?
The future of healthcare will be vastly different from how we have visualized it. Goodbye gentle-mannered family physician and welcome robotic arms performing surgeries and machines sifting medical histories. Still, the possibility of a robot performing surgery with his metallic fingers fills me with fear. For now I can relax as the feedback is that we still have a long way to go before robots have enough dexterity and sensitivity to perform surgeries autonomously. At this point, there’s almost always a highly-skilled surgeon at the other end who is in total control. There are some who believe that the role of doctor or surgeon may become superfluous in a short span of time, as AI can diagnose and treat illness and injury more accurately and faster. But to interpret information or to break bad news calmly, I think human intervention will be necessary.
AI in the healthcare business is useful at the macro level – to manage epidemics and predict patient outcomes. There will be a shifting of skills, but I think there should be a balance between humans and machines. Because, human concern, experience (that is so much more than a data repository), and common sense cannot be replicated by machines.