A new AI-based model has been developed to predict an individual’s risk of developing osteoporosis by analyzing factors such as weight, age, grip strength, blood pressure, and lifestyle habits. The model, created by researchers at Tulane University, uses a deep learning algorithm and real-world health data from over 8,000 participants to identify key risk factors. Early detection of osteoporosis risk through this model could lead to better outcomes for patients by allowing for preventative measures. The researchers aim to make the model accessible to the public for predicting osteoporosis risk and empowering individuals to seek treatment to strengthen their bones. Further development and refinement are needed before the AI-based platform can be widely used. The study detailing the model has been published in the journal Frontiers in Artificial Intelligence. The lead author, Chuan Qiu, emphasizes the importance of early detection and intervention in managing osteoporosis risk. The model has the potential to improve patient outcomes and reduce the impact of osteoporosis on individuals’ health.
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AI model predicts osteoporosis risk, developed by scientists. #HealthTech
