Artificial intelligence: Potential to improve knee arthritis care

                               Although artificial intelligence is upending medical care, its potential applications to orthopedic surgery haven't been widely studied. Mayo Clinic found that a deep learning algorithm can identify and classify knee osteoarthritis on radiographs as accurately as fellowship-trained knee arthroplasty surgeons.

                               "This technology has the potential to significantly decrease the likelihood of inaccurate assessment of radiographs in the diagnosis and treatment of knee arthritis," says Adam J. Schwartz, M.D., an orthopedic surgeon at Mayo Clinic in Phoenix/Scottsdale, Arizona. "There is currently no standardized approach, and quite a bit of variability, in reading these radiographs. Reducing that variability can facilitate clinical decision-making and improve outcomes for patients."

The surgeons' ratings were compared to one another and to the neural network's ratings of those 576 knees. Statistical analysis found broad agreement between the assessments from the surgeons and the artificial intelligence tool.

Deep visual learning                         

    A convolutional neural network is a type of deep learning tool that is commonly used to evaluate visual imagery. Deep learning is a method of artificial intelligence that processes raw data — such as images — with learning algorithms to create layers of nodes, each receiving information from, and learning from, the other.

"Before implementing this type of solution in clinical practice, we need more data and additional training, to minimize the potential for errors in classifying the severity of osteoarthritis," Dr. Schwartz says. "But once you have an artificial intelligence model, you can find all sorts of ways to improve efficiency and reduce variability."

       

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