Organisation profile
Organisation profile
The Deep Digital Phenotyping Lab aims to develop key expertise and skills in the entire chain of research in digital health
The digitization of health care is transforming the way diseases and populations are characterised and monitored. It enables more personalised health care to be provided by taking into account the physiological and contextual specificities of individuals. To move towards precision health, it is necessary to develop innovative study models and approaches that encompass digital, biological, clinical and omics data. All these data would allow for more accurate characterisation of diseases and populations.
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Collaborations and top research areas from the last five years
Profiles
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Sybille Barvaux
- Deep Digital Phenotyping Research Unit - Digital Health Scientific Manager
Person: Employee
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IMPHEENITY: Immuno-Phenotyping for Better Cardiovascular Risk Prediction In People With Type 1 Diabetes
Fagherazzi, G. (PI), Pizzimenti, M. (Project Manager), Aguayo, G. (Partner) & Bour, C. (Partner)
1/09/25 → 31/08/28
Project: Research
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Voice AI Labs: Voice AI Labs
Fagherazzi, G. (PI), Fünfgeld, K. (Partner) & Fischer, A. (Partner)
1/06/25 → 31/05/27
Project: Research
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Xpose (Maurane Rollet): Associations between exposomic phenotypes, glycemic variability and complications in people with type 1 diabetes
Fagherazzi, G. (PI) & Rollet, M. (PhD Student)
FNR - Fonds National de la Recherche
1/11/24 → 31/10/28
Project: Research
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Data-driven clinical decision support tool for diagnosing mild cognitive impairment in Parkinson’s disease
NCER-PD Consortium, 12 Jan 2026, In: npj Parkinson's Disease. 12, 1, p. 15 15.Research output: Contribution to journal › Article › Research › peer-review
Open Access -
A Functionally-Grounded Benchmark Framework for XAI Methods: Insights and Foundations from a Systematic Literature Review
Canha, D., Kubler, S., Främling, K. & Fagherazzi, G., 14 Jul 2025, In: ACM Computing Surveys. 57, 12, 40 p., ART320.Research output: Contribution to journal › Article › Research › peer-review
Open Access2 Citations (Scopus) -
A nationwide 12-month observatory of automated insulin delivery shows improved glucose control, sustained adoption, and reduced acute severe events
Riveline, J. P., Julla, J. B., Bonnemaison, E., Joubert, M., Lablanche, S., Gazagnes, A. S., Demarsy, D., Gouet, D., Schaepelynck, P., Amouyal, C., Vale, F. D., Schletzer-Mari, A., Clavel, S., Spiteri, A., Campinos, C., Favre, S., Tauveron, I., Mathivon, L., Borot, S. & Fagherazzi, G. & 31 others, , 24 Nov 2025, (E-pub ahead of print) In: Diabetes, Obesity and Metabolism. 28, 2, p. 1179-1190 12 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access1 Citation (Scopus)