Healthcare has once again fallen under the spotlight, given the current global situation. Medical science has undoubtedly improved rapidly, extending life expectancy across the globe. But as people live longer, medical systems are witnessing vast growth in demand for services, which jacks up the cost and pushes the healthcare workforce to deliver top-notch services to the patients.
Automation is among the most crucial tech breakthroughs in the sector, and Artificial Intelligence (AI) is a powerful tool to let to success. But when it comes to healthcare, there is a common myth: With AI, we are expecting robots to take over doctors and nurses, rendering people obsolete. Patients may entrust to machines – rather than doctors – to make difficult decisions.
However, AI is not replacing doctors. Instead, it is helping them improve diagnostic accuracy and efficiency. Artificial Intelligence does its work in accessing substantial data sets of potentially life-saving information, such as treatment methods and their outcomes, and other data like survival rates, etc.
Therefore, incorporating AI into clinical workflow helps streamlining medical procedures for doctors. The ultimate goal is to work with doctors and medical professional to improve healthcare services via the fair use of AI. On this front, three significant developments are expected.
The first one is medical imagery analysis, which is one key area that requires an upgrade with the support of AI. Primary medical imaging represents a tremendous potential for growth due to its increasing demand. With the help of AI, such imaging service gets a significant boost in resolving the mismatch of demand and supply among the current medical services.
In some countries, there are as many as two-thirds of primary hospitals serving merely 20% of patients requiring diagnosis and treatment. There could be some 10% of the medical institutions classified as tertiary, where more than a third of patients are seeking service there.
The resource mismatch represents another trend – AI empowers the primary medical service, further alleviating the imbalance between supply and demand of existing medical services. And the shortage of radiologists in primary medical institutions is getting more alarming than ever.
Further observed in the area of medical imagery is the combination of hardware and software. The integration of AI algorithm and hardware is imperative, breaking through the physical limitations of hardware and improving the intelligent density, measured by computing power per unit area.
Simply put, the AI algorithm works with hardware to boost intelligence density and lower the cost of building up the system. The demand for computing, meanwhile, will keep going up to meet the AI requirements for various scenarios in the new digital era. For AI to work effectively, it takes both software and hardware together – neither one could handle alone.
So with the power of AI, the application of imagery is brought to another level, where radiologists have more significant roles in the clinical decision-making process. Intelligence diagnosis systems are now used in chest examination, mammography, and for child’s growth and development, so that radiologists can have more participation in giving advises upon the results.
