You are invited to join us on Thursday, February 18, 2021, 10 – 11 AM, for an intriguing seminar by Christophe Lambert, PhD, Associate Professor, Department of Internal Medicine, Center for Global Health, Division of Translational Informatics.
Dr. Lambert will present on A Validated Machine Learning Model of Conversion from Major Depressive Disorder to Bipolar Disorder.
This will be a virtual seminar hosted via Zoom. Please register in advance here: https://hsc-unm.zoom.us/meeting/register/tJwsdOispjkvHN2XTPtGTajxOUnPfI_yWzsd
Background: A high fraction of patients with bipolar disorder are first diagnosed with major depressive disorder, and may receive inappropriate treatment. Starting with a complex set of thousands of variables, we created a parsimonious 9-variable machine learning model using 5 large-scale US patient record databases, and successfully validated it across 8 national and international databases. The model can be scored with a pencil and paper, and provides insight into what factors place patients at higher risk of conversion.
Learning objectives:
1. To understand how machine learning models can be developed on patient record data, and validated across an international network.
2. To understand factors driving the high conversion rate from an initial diagnosis of major depressive disorder to a subsequent diagnosis of bipolar disorder.
The University of New Mexico School of Medicine designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
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