THE OSTEOARTHRITIS PROBLEM
Osteoarthritis is the first global cause of permanent disability. It is estimated that 300 million people are diagnosed with this condition worldwide. By the year 2040, an estimated of 78.4 million adults aged 18 years and older will have doctor-diagnosed OA in the United States alone. OA is the second most costly health condition treated at US hospitals, it accountes for $16.5 billion, or 4.3%, of the combined costs for all hospitalizations.
Existing OA diagnosis systems are inevitably limited to the observation capacity of the radiologist. Because of this, early stage pathology and superficial tissue lesions can’t be reliably identified wile diagnosis of mid to advanced stages of tissue degeneration remain subject of errors up to 30%.
01 / EXTRACT
Relying on machine learning techniques we extract anatomical and physiological markers of multiple joint tissues from pixel patterns and textures contained in Magnetic Resonance Images (MRI).
02 / PROCESS
Features significantly correlated to pathological and clinical aspects are added to selected tissues. The data is processed classified and contrasted with aggregated information for further insight.
03 / DISPLAY
Relevant elements influecing diagnosis and prognosis are presented in ditail. Patient data is displayed with average normality parameters and patiend lesions can be explored and shared in 3d.
Boris Panes (Chief of Data Science): PhD. Physics PUC-Chile. PhD. Physics PUC-Chile. Experienced in deep Learning and automation of complex systems.
Carlos Andrade (Chief of Engineering): PhD. Biomedical Engineering PUC-Chile. Expert in medical electrical signals and magnetic resonance image processing.
Cristobal Varela (Chief of Medical Imaging): Musculoskeletal radiology. Interventional Radiologist, Clínica Universidad de los Andes.
Germán Norambuena (Chief of Traslational Medicine): Orthopeadic Hip and Knee Surgeon Clínica Universidad de los Andes. Fellow, Stem Cell and Biomaterials. Mayo Clinic, Rochester.
Javier Urzúa (CEO): Master of Business Administration, University of Queensland Australia. Founder of two MedTech companies.