New Delhi, July 1 (PTI) – A groundbreaking study has introduced a new model capable of predicting an individual’s likelihood of developing osteoporosis, a condition where bones weaken and become brittle.
Researchers from Tulane University in the US have developed this AI-based model by analyzing real-world health data from over 8,000 participants aged 40 and older. The study, part of the Louisiana Osteoporosis Study, identified the ten most critical factors for assessing osteoporosis risk. These factors include weight, age, grip strength, blood pressure, and habits such as smoking and alcohol consumption.
Deep learning, a form of artificial intelligence, powers this model by mimicking the human brain to detect patterns in large datasets. According to the study published in the journal Frontiers in Artificial Intelligence, this technology could lead to earlier diagnoses and better outcomes for those at risk of osteoporosis.
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Lead author Chuan Qiu, a research assistant professor at the Tulane School of Medicine, emphasized the importance of early detection. “The earlier osteoporosis risk is detected, the more time a patient has for preventative measures,” said Qiu.
However, the model is still in development and requires further refinement before it can be made publicly available. Qiu added, “Our final aim is to allow people to enter their information and receive highly accurate osteoporosis risk scores to empower them to seek treatment to strengthen their bones and reduce any further damage.”
This advancement holds promise for improving the early detection and management of osteoporosis, potentially benefiting countless individuals in maintaining better bone health.
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