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In Silico Clinically-Viable Assistive Tools for Prediction and Rehabilitation of Knee Osteoarthritis

CORDIS · observation · Publication date unknown

eared towards out-of-lab and clinical use for predicting KOA progression in different functional activities, allowing personalized rehabilitation. The multiphysics computational models, assisted with artificial intelligence (AI), will be validated at different spatial scales using in vitro tissue and cell level experiments and in vivo joint loading and quantitative medical images. This multidisciplinary project bridges together complementary skill sets of Dr. Esrafilian, Profs. Korhonen’s and Delp’s teams, with their expertise in biomechanics, computational modeling, biochemistry, biology, and AI. The beyond state-of-the-art models of this research can make a profound impact on early-stage KOA prediction and treatment planning, potentially increasing the quality of life in KOA individuals and reducing the need for surgical interventions. articular cartilage, knee osteoarthritis, finite element modeling, neuromusculoskeletal modeling, artificial intelligence, image processing, mechanobiology, predictive model

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recordType

award

status

SIGNED

region

EU

value

302331.36

unit

EUR