The healthcare industry is changing in the face of new innovations and technologies. A study published in the American Journal of Medicine points out how these changes are only a small fraction of what is to come for health practitioners and patients across the globe, as artificial intelligence (AI) continues to improve.
The study details AI applications and a popular subdiscipline — machine learning (ML). ML works with massive volumes of data, known as big data, and identifies patterns and interactions among them to generate useful associations. It has been used in the financial and insurance industries to tighten security measures and identify fraud before it happens. Special Counsel notes how AI is used in the legal industry to pinpoint relevant data and remove duplicate records on a grand scale for litigations. And in healthcare AI is helping to automate clinical decision systems. However, experts suggest that is just the beginning, and AI will continue to disrupt many more industries in the coming years.
Not only will robotic surgeries result in more precise operations, they will also be able to draw data from AI and ML techniques to improve important decisions. Surgeons can rely on AI in the future to show real-time data and how it is affected by existing medical records, as well as information about previous surgeries conducted by other surgeons. Fortune reports that this kind of AI-enabled robot surgery could save the healthcare industry $40 billion annually by 2026.
AI is currently focused on identifying more life-threatening diseases like cancer or cardiovascular ailments. In the future, its application will also help predict and diagnose chronic illnesses such as diabetes. Clinical insights will be calculated by AI based on ML techniques taken from medical records from all over the country. Considering how the Internet of Things is currently disrupting the healthcare industry, patients and hospitals should expect a reduction in costs, shorter stays, and healthcare outcomes to improve thanks to these technologies.
Testing and developing drugs can be very costly with mostly low success rates, with researchers from the Massachusetts Institute of Technology estimating that only 14% of new drugs make it to the market. What’s more, 25% of all discovered drugs were found by chance or by accident in laboratories. Science Focus lists some of the most popular accidental drug discoveries which include penicillin, birth control, and Viagra. That being said, with AI and ML being used as cross-referencing tools, there will be a wealth of information available to developers that leaves less to chance. This information will provide them invaluable data about possible side effects and the potential of new drugs based on the massive amount of data that AI can process. All this will result in higher success rates and more useful drugs available to the public at a faster and more efficient pace.
While these transformative applications of AI in the healthcare industry look promising, there are still a significant number of steps that have to be taken to get there. For one, AI and data science in general are facing harsh criticisms about their treatment of user information and the ethical ramifications attached to these processes.
More work has to be done on the government’s part to implement policies that will outline which information is meant to remain private, and AI scientists and innovators must learn to tread the ethical line set out for them by the public. In the meantime, patients and doctors can enjoy the current applications of the new technology, which makes life and treatment a lot easier than it was a few years ago.