Department of Urologic Sciences, Faculty of Medicine
Faculty (G+PS eligible/member)
Urology; Computer engineering; Civil engineering, n.e.c.; Biomedical instrumentation (including diagnostics); Medical devices; Artificial tissues engineering; Biomedical robotics; Image guided surgery systems; Applied immunology (including antibody engineering, xenotransplantation and t-cell therapies); Transplantation immunology; kidney transplantation; patient reported outcomes; medical apps for mobile health; machine learning analytics of medical imaging; machine learning analytics of complex medical data outcomes; Robotics; quality in healthcare; environmental impact of healthcare; Artificial Intelligence in Healthcare; planetary health intersection with healthcare; kidney transplantation, patient reported outcomes, medical apps for mobile health, machine learning analytics of medical imaging, machine learning analytics of complex medical data outcomes, robotics, quality in healthcare, environmental impact of healthcare, artificial intelligence in healthcare, planetary health intersection with healthcare