Computer and life sciences are very dynamic fields of interdisciplinarity to develop new diagnostic and therapeutic techniques used in precision medicine. Identifying new biomarkers and integrating them in phenotyping models require a strong medical, technological and data science expertise justyfing collaborations between INSB and INS2I teams.
Through a common PhD thesis the Labri and SANPSY have been able to identify new vocak biomarkers able to predict subjective and objective measure of sleepiness (EEG recordings). Fatigue, sleepiness and sadness are strong clinical components of mental disorders and vocal analysis can bring very novative markers of these symptoms. Our project will generate on healthy subjects and pateints new a personalized phenotyping methods taking into account physiological, behavioral, and ecological biomarkers. To do so, we propose a 3 dimension joint program :
1: Data collection through different new ecological modalities (i.e. voice and speech analysis),
2: Definition and extraction of specific indicators/criteria to define optimal patients phenotypes,
3: Patients classification through big data analysis to predict therapeutic responses.
