Today, the use of Artificial Intelligence in the healthcare sector continues gaining traction, with promising applications like disease management, data collection, and organization, and cost reduction. Its use in healthcare is to find out, diagnose, and treat diseases. Its capabilities have already impacted research teams globally that are developing algorithms to detect and warn of wicked cells long before a physician’s eye could make the diagnosis. These algorithms are powered by Deep Learning that enables the program to learn from patterns and previous diagnoses.
AI could greatly improve the prognosis for a disease like malignant mesothelioma. Moreover, research firms identify the need to develop tailored AI to defined rare diseases and have also made grants available for this specific purpose. Apart from these significant advancements, AI is not a phenomenon cure for all of healthcare’s issues. Since with any innovation, it also presents a host of own issues that will require addressing before its full integration, including deployment cost, lack of regulations, and technological failures and shortcomings. However, market insights predicted that AI in healthcare could save USD52 billion by 2021. Also, the cost of actually purchasing these complicated machines will be not easy for healthcare centers. That could generate a disparity in quality of care for diverse populations without access to the hospitals that can afford AI machines.
Moreover, finding ways to streamline this system can save both money and lives, and making the scramble for industry-disrupting technologies quite competitive. Additionally, healthcare is the ever-evolving field with liability and regulations, where AI and other promising technologies seem to be the most evolving systems.