Publicações científicas.
Pesquisa em transtorno bipolar, biomarcadores e aplicações de machine learning em saúde mental — desenvolvida durante doutorado (UFRGS) e pós-doutorado (McMaster University).
Doutorado e produção acadêmica
- Neuron-glia Interaction as a Possible Pathophysiological Mechanism of Bipolar Disorder.
- Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.
- The impact of machine learning techniques in the study of bipolar disorder: A systematic review.
- Differential biomarker signatures in unipolar and bipolar depression: A machine learning approach.
- Bullying and psychotic symptoms in youth with bipolar disorder.
- Neuroprogression and illness trajectories in bipolar disorder.
- Clinical differences between patients with pediatric bipolar disorder with and without a parental history of bipolar disorder.
- Risk factors for suicidality in patients with panic disorder: A systematic review and meta-analysis.
- Prediction of depression cases, incidence, and chronicity in a large occupational cohort using machine learning techniques: an analysis of the ELSA-Brasil study.
- The Early Burden of Disability in Individuals With Mood and Other Common Mental Disorders in Ontario, Canada.
- Structural and Functional Brain Correlates of Neuroprogression in Bipolar Disorder.
- Potential use of text classification tools as signatures of suicidal behavior: A proof-of-concept study using Virginia Woolf's personal writings.
- Ethics in the Era of Big Data: Big Data Analytics in Mental Health.
- Accelerated aging signatures in subjects with schizophrenia and their unaffected siblings.
Tese acadêmica
Psiquiatria preditiva e personalizada: aplicações de técnicas de machine learning em saúde mental — Universidade Federal do Rio Grande do Sul, 2020.