PRECISAI - Precision Psychiatry and AI for Early Intervention and System Innovation in Affective Disorders.
My research seeks to advance understanding of how mood disorders develop and affect the brain, body, and daily life over time. I focus on creating actionable tools that harness clinical data to detect early warning signs—empowering patients and clinicians to intervene before full-blown episodes arise.
Through our program, PRECISAI, we integrate insights from patient care with cutting-edge technologies including artificial intelligence, digital monitoring, and biomedical data. By analyzing electronic health records, biomarkers, and data from wearable devices, we aim to characterize the progression of bipolar and related affective disorders.
Our goal is to facilitate early identification, deepen scientific understanding of these conditions’ trajectories, and develop tailored, evidence-based interventions that are precise, scalable, and suited to real-world clinical environments. In doing so, we strive to meaningfully improve the lives of individuals at risk for, or living with, mood disorders—as well as the wellbeing of their families.
Selected topics of interest:
Bipolar and other affective disorders | Artificial intelligence in mental health
Digital technologies in mental health | Machine Learning algorithms
Electronic Health Records (EHR) big data | Precision Psychiatry
Early Intervention | Youth Mental Health
Inflammation and cardiometabolic biomarkers | Bio-digital signatures
Curious minds welcome. If you're a clinician or researcher who shares these goals, we warmly invite you to connect with our vibrant research group. We value innovation, thrive on collaboration, embrace the Francophonie, and pursue rigorous inquiry, always eager to explore new frontiers together.
I am a tenacious and inquisitive German-Brazilian physician dedicated to enhancing the quality of life for individuals living with mood and other mental health disorders. My work is grounded in a dual commitment to rigorous research and compassionate, patient-centred care.
My scientific interests lie in understanding how mood disorders evolve over time—how they affect the brain, body, and day-to-day functioning. I focus on creating actionable tools that harness clinical data to detect early warning signs—empowering patients and clinicians to intervene before full-blown episodes arise.
Currently, I serve as a Staff Psychiatrist at The Ottawa Hospital and hold academic appointments as Associate Professor in the Department of Medicine at the University of Ottawa, and Associate Scientist at both The Ottawa Hospital Research Institute (OHRI) and the CHEO Research Institute.
I earned a dual PhD in Psychiatry and Neurosciences through internationally recognized postgraduate programs at INSERM (France) and UFRGS (Brazil), followed by postdoctoral fellowships at the Pasteur Institute and CNRS in Paris. My clinical and research journey spans multiple countries and health systems, allowing me to bring a globally informed perspective to my practice—fostering innovative, collaborative, and culturally attuned approaches to mental health care and discovery.
M. Nanda, D. Inkpen and
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Dargél, A. A., Mosconi, E., Masson, M., Plaze, M., Taieb, F., Von Platen, C., Buivan, T. P., Pouleriguen, G., Sanchez, M., Fournier, S., Lledo, P., & Henry, C. (2020). Toi meme, a mobile health platform for measuring bipolar illness activity: Protocol for a feasibility study. JMIR Research Protocols, 9(8), e18818. https://doi.org/10.2196/18818
Dargél, A. A., Volant, S., Brietzke, E., Etain, B., Olié, E., Azorin, J., Gard, S., Bellivier, F., Bougerol, T., Kahn, J., Roux, P., Aubin, V., Courtet, P., Leboyer, M., & Henry, C. (2020). Allostatic load, emotional hyper-reactivity, and functioning in individuals with bipolar disorder. Bipolar Disorders, 22(7), 711-721. https://doi.org/10.1111/bdi.12927
Dargél, A. A., Roussel F, Volant S, Etain B, Grant R, Azorin JM, M'Bailara K, Bellivier F, Bougerol T, Kahn JP, Roux P, Aubin V, Courtet P, Leboyer M; FACE-BD Collaborators, Kapczinski F, Henry C. Emotional hyper-reactivity and cardiometabolic risk in remitted bipolar patients: a machine learning approach. Acta Psychiatr Scand. 2018; 138 (4): 348-359. doi: 10.1111/acps.12901.
