LANSING, Mich. (WILX) – Artificial intelligence has allowed physicians to receive better training, diagnose diseases and give patients more control over their surgery outcomes.
For 33-year-old Meredith Goode, running is her passion.
“I have done a ton of half marathons and marathons,” Goode said. “I was into ultra-running, super into triathlons.”
But when she was training for a 100-mile race, she noticed something didn’t feel right.
“I was just experiencing some groin pain and some really shooting pain down my left leg and into my back,” she recalled.
An MRI revealed it was a labral tear, which is an injury to the tissue that holds the ball and socket parts of the hip together.
“The thing that bothers most patients the most is they can’t do the activities that they typically do,” said Dr. Shane Nho.
Nho recommended Goode have hip surgery and before the surgery, he was able to predict the likelihood Goode would be able to get back to her level of fitness after surgery by using a machine learning algorithm. Nho and his team based the algorithm on a database with information collected from patients before and after surgery that contains age, surgical history, level of activity and the patient’s reported outcomes.
“Having this data and this algorithm, we’re able to basically calculate it to give the patient a percent of likelihood of achieving a significant improvement in terms of overall outcomes,” Nho said.
Having that information placed Goode’s mind at ease.
“I wasn’t sure if the surgery would kind of impact what I had been doing,” Goode said. “Knowing his confidence gave me more confidence that it would be a success.”
Goode was pain-free and running six months after surgery. A year later, she was ready to run again in marathons.
The algorithm is only applicable to a certain type of hip surgery, which is hip arthroscopy. However, Nho said he is looking to roll the algorithm out in other procedures.
More: Health stories
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