By Bruce Lieberthal
I often speak or write about AI in health care. What surprises me is how quickly AI evolves; each time I present, the information changes significantly.
The growth of AI is driven by advances in technology, including powerful computers and data analysis techniques, which enable machines to learn from large amounts of information.
Despite the current buzz around AI, the concept was initially crystallized in the 1950s, first at Dartmouth and then at Massachusetts Institute of Technology and Stanford. Almost immediately, AI’s pioneers looked at applying machine intelligence to health care by creating software algorithms initially labeled as expert systems – solutions that, through a guided Q&A, helped doctors of varying experience levels get expert answers regarding diagnostics and treatment recommendations.
AI’s future in health care is fundamental to both health care providers and the industry. Several key dynamics drive AI in health care, including:
- The demand by patients and providers for speed and convenience while retaining a human touch.
- Expectations for more personalized treatment and experiences.
- Pressure to achieve enhanced operational excellence and efficiency in the health care delivery system.
- The need to improve access to care.
- The desire for privacy and security.
- Requirements of an intensifying regulatory environment.
- Advancements in research and technology.
Health care is one of the key industries that will see tangible and profound benefits from AI. Let’s review the most significant advancements.
2D and 3D imaging analysis: Computer vision AI
Much of 2D/3D imaging analysis uses computer vision AI. Computer Vision is AI that can recognize patterns in images. In health care, these images are photographs, radiographs, CTs, MRIs, etc. Computer vision solutions are already important in medicine and dentistry, mostly in diagnostics.
As technology continues to improve, giant leaps will be made in the automation of diagnosis and treatment planning. This can help reduce medical errors and adverse events, and result in greater image resolution, resolving signs invisible to both humans and digital systems today. In turn, these advancements contribute to enhanced speed and precision for diagnosing medical and dental diseases, while helping to reduce the risk of health care emergencies.
New uses of AI in 2D and 3D imaging include:
• AI, Imaging, and Digital Production: AI in imaging will enable vast leaps in digital production, especially within the practice (e.g., 3D printing). Devices and software associated with digital production will be working with, or embedding, AI imaging.
