Intelligent Spine Surgery: Improving Accuracy through Predictive Analytics
Artificial Intelligence (AI) is expected to save US Healthcare $150 billion annually by 2026. Connected technologies, preliminary diagnosis tools, and intelligent assistants are among the top ten drivers. For surgeons, AI-powered predictive analytics can help understand preoperative risk, increase efficiency, and improve patient outcomes.
Technologies transforming education in spine surgery
Being a spine surgeon requires the dedication, training, and focus of a professional athlete with significantly more at stake – patients’ lives. Spine surgery can be complex, and patient and surgeon training is a continuous learning process. New technology is helping advance this process.
Reducing Orthopedic Burnout with AI: How Henry Ford Can Help
Henry Ford is associated with intelligence, but not artificial intelligence (AI). After all, AI was born a year before his death. However, in his heyday, Ford went against popular opinion and introduced innovative ways to reduce employee burnout in his factories. This type of disruptive innovation is what AI can bring right now to help heal the U.S. healthcare system, including the field of Orthopedics.
AI in Medical Devices: Top 3 Trends you Need to Know
Medical device companies must meet customer expectations, continue innovating, and stay competitive while lowering costs.
AI-Powered Technologies such as Robotics Will Help Improve Orthopedics
Robotics are an integral part of the future of surgery. Without finding technology-driven solutions for the OR, we will continue facing surgeon burnout.
The Evolution of Intelligent Surgery
The introduction of artificial intelligence is affecting a change in musculoskeletal medicine – an evolution from traditional orthopedic surgery into Intelligent Surgery.
Building Artificial Intelligence on Health Data
Artificial intelligence is built on strong data strategies, but exchanging protected health information through an EHR system is a challenge. Electronic health records are restricted by privacy compliance and low device interoperability. Technology companies are developing ways to collect and apply data throughout clinical workflows.
