• One Gustave L. Levy Place

    10029-6574 New York

    United States

Calculated based on number of publications stored in Pure and citations from Scopus
20202025

Research activity per year

Personal profile

Biography

Dr. Isotta Landi is Assistant Professor in the Department of Medicine at the Icahn School of Medicine at Mount Sinai. She is affiliated to the Mount Sinai Clinical Intelligence Institute (MSCII) and she is Head of the data science branch of the Blau Center, the consultation and treatment center for psychosis at Mount Sinai.

Dr. Landi received her B.Sc. in Mathematics from the University of Pisa (Italy) and M.Sc. in Mathematics from the University of Trento (Italy). She earned her PhD in Computational Psychology at the University of Trento working jointly with the Laboratory of Observation Diagnosis and Education and the Laboratory of Predictive Models for Biomedicine and Environment (Bruno Kessler Foundation). She then underwent two years of postdoctoral research training during which she worked first at the Laboratory for Autism and Neurodevelopmental Disorders, Italian Institute of Technology supervised by Michael V. Lombardo, PhD (1 year) and then at the Laboratory of Brain and Data Sciences, Department of Psychiatry at the Icahn School of Medicine at Mount Sinai mentored by Alexander W. Charney, MD, PhD (1.5 years).

Dr. Landi’s research focuses on the investigation of clinical and genetic factors associated to different outcomes of patients with psychotic disorders in real-world healthcare settings. Her long-term goal is the implementation of computational tools that can enable data-driven individualized therapeutic decisions to support clinicians in their daily practices. She currently focuses on natural language processing methods for clinical notes mining towards the identification of clinical sub-phenotypes (e.g., antipsychotic efficacy and safety) of schizophrenia and related psychotic conditions in large health systems to increase the power to detect associations for both clinical and genetic features.

Headline

ASSISTANT PROFESSOR | Medicine, Data Driven & Digital Medicine

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