Artificial Intelligence-based Voice Assessment of Children and Adults Respiratory Conditions

Acute and Chronic respiratory conditions represent a leading cause of death and morbidity in children and adults worldwide. The diagnosis of bronchiolitis and asthmatic exacerbations is based on clinical, and mostly subjective, clinical parameters with moderately accurate prognostic role. Patients undergoing neck radiotherapy need invasive assessments of larynx. A simple biomarker like Voice may facilitate the management of these conditions. Recent studies showed that VOICE may be used as a good and easy biomarker to diagnose and monitor several respiratory and non-respiratory conditions. A prospective study aimed to collected VOICE and other clinical data in adults and children with common acute and chronic respiratory conditions at high impact on healthcare systems will be performed. VOICE-omic data will be linked with clinical findings generating data integration, using artificial intelligence technology to develop a Decision Support Systems to provide the basis for non-invasive personalised early recognition, diagnosis, monitoring and prognosis of patients with these conditions.