Multidisciplinary Center for Infectious Diseases (MCID)

menoBalance App: Use of AI methods to design a personalised chronic and infectious disease management medical device

Lead Applicant: Prof. Dr. med. Petra Stute (Cluster: Patient-Focused Research)

Gynecological Endocrinology and Reproductive Medicine, Department of Obstetrics and Gynecology

Co-Lead Applicant: Prof. Dr. David Ginsbourger (Cluster: Patient-Focused Research)

Mathematical Physics and Actuarial Science

Co-Applicant: Dr. Ben Spycher (Cluster: Epidemiology)

Institute of Social and Preventive Medicine (ISPM)

Co-Applicant: Dr. Rowan Iskandar (Cluster: Economics)

SITEM Center for Translational Medicine and Biomedical Entepreneurship

Menopausal women are at high risk for infectious disease (ID), including COVID-19. Their concomitant increase in chronic non-communicable diseases including cardiovascular disease or diabetes will keep them at particular risk in future pandemics. Common respiratory tract infections are suitable models for defining and detecting ID predictors ("red flags"). This project aims at developing a digital medical device app ("Navina+") for menopausal women. Navina+ will receive data from a smart tracker. Based on machine learning models, it will: 1) create personalized risk assessments for chronic disease development; 2) provide early warnings ("red flags") for potential respiratory infections (e.g., colds, flu, COVID-19).