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NRIPage | Articles | AI Pioneer from Telangana Develops 94% Accurate Bone Degeneration Detection Model | Get General Articles. Stay Informed on a World of Topics - NRI Page
Rahul Trivedi, a 33-year-old researcher from Telangana, has developed an AI model that detects bone degeneration with an impressive 94% accuracy. His work has the potential to revolutionize orthopaedic care by enabling early diagnosis and optimizing treatment strategies. Currently pursuing a PhD at Colorado State University and serving as a Senior Systems Architect at Verizon, Rahul has been dedicated to integrating AI with medicine to improve healthcare outcomes.
Rahul’s AI model analyzes X-ray images to detect bone degeneration more accurately than traditional methods. His model surpasses existing techniques, with CNN-based detection achieving 91.2% accuracy and Transfer Learning reaching 92%, while his model records an improved 94.5% accuracy. This advancement allows doctors to detect knee degeneration early, improving patient care and facilitating faster recoveries through timely interventions.
Expanding AI Applications in Healthcare
In addition to his work in orthopaedics, Rahul holds a patent for an AI-driven wearable health monitoring device (Design No. 6409910, UK). This device tracks exercise patterns and provides early health alerts, promoting preventive care. His AI research also extends into oncology, where he collaborated with oncologists at Moffitt Cancer Center to develop AI tools for cancer diagnosis and treatment planning, reinforcing AI's role in modern medical applications.
Rahul’s journey from Khammam, Telangana, to global recognition highlights his dedication to AI-powered healthcare advancements. He completed his B.Tech at JNTU Hyderabad in 2012 and later earned a Master’s degree from the University of Central Missouri in 2015. With a vision of making AI-driven healthcare solutions more precise and accessible, Rahul continues to pioneer innovations in orthopaedics, oncology, and neurology, setting new benchmarks for AI-assisted medical diagnostics worldwide.
