Respire - Responsible Explainable Machine Learning for Sleep-related Respiratory Disorders
Selected for funding by the Research Council of Norway in the "Fellesløft IV" framework (2022 - 2026).
Respire seeks to address the opportunities and risks that arise in the social-technological context of using Machine Learning (ML) in the health domain. With novel low-cost health monitoring solutions and explainable ML (xML) we aim to (1) improve the diagnostic process of sleeprelated respiratory disorders, (2) enable long-term monitoring of patients, and (3) gain new knowledge concerning these disorders and personalized treatment. Ethical, legal, and technological guidelines and an explainability framework shall be established to enable the systematic development and evaluation of responsible xML for such disorders. It is the goal to understand the implications of low-cost monitoring solutions and xML for patients, medical personnel, the health sector, and society and to solve fundamental epistemic-ethical challenges, data protection concerns, and other regulatory challenges that are introduced by new mHealth solutions.