New Delhi: A newly developed model could predict According to a study, an individual’s chances of developing osteoporosis, in which bones break down and become weak and brittle, are significantly lower. By testing the AI-based model on real-world health data from people, researchers identified the top ten factors for predicting osteoporosis risk, including weight, age, and grip strength, along with blood pressure and smoking and alcohol drinking habits.
For the model, researchers from the Tulane UniversityThe United States created a deep learning algorithm using data from more than 8,000 participants ages 40 and older in the Louisiana Osteoporosis Study at the same university.
A form of artificial intelligence, deep learning algorithms mimic human brains to find trends in large data sets.
Use of the model could potentially lead to earlier diagnoses and better outcomes for patients with risk of osteoporosisaccording to the authors of the study detailing the model, which is published in the journal Frontiers in Artificial Intelligence.
“The earlier the risk of osteoporosis is detected, the more time the patient has to… precautionary measures“said senior author Chuan Qiu, a research assistant professor at Tulane School of Medicine.
The model requires further work before the AI-based platform can be used by the public to predict the likelihood of developing osteoporosis, Qiu said.
“Our ultimate goal is to allow people to enter their information and receive highly accurate osteoporosis risk scores to allow them to seek treatment to strengthen their bones and reduce any further damage,” Qiu said.
