2024 Strategic Grant (SG)
Developing ML-Based Risk Prediction Model for Cognitive Impairment in Geriatric Patients in Acute Care Settings
laili Soleimani
Icahn School of Medicine at Mount Sinai
New York, NY - United States
Susceptibility of patients with dementia and cognitive impairment to complications and the growing emphasis on early intervention strategies highlights the importance of identifying at risk population. Led by Dr. Laili Soleimani at Mt Sinai, this study is a single-centered and retrospective study at the Mount Sinai Hospital utilizing real-world data (RWD) including structured (Lab, vitals, and nursing evaluations) and unstructured (progress/care notes, radiology reports, pathology reports) from the Electronic Medical Record (EMR) data to build machine-learning technology to predict cognitive impairment among individuals based on Mini-mental State Exam (MMSE) score. The development and implementation of this digital tool is an example of translational research leveraging RWD to answer questions pertinent to dementia. Learnings from this study will inform how real world data is used when data is missing, and will help inform ALZ-NET considerations as we expand more broadly to electronic health records.