Papers › Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records
Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records
Tanish Tyagi, Colin G. Magdamo, Ayush Noori, Zhaozhi Li, Xiao Liu, Mayuresh Deodhar, Zhuoqiao Hong, Wendong Ge, Elissa M. Ye, Yi-han Sheu, Haitham Alabsi, Laura Brenner, Gregory K. Robbins, Sahar Zafar, Nicole Benson, Lidia Moura, John Hsu, Alberto Serrano-Pozo, Dimitry Prokopenko, Rudolph E. Tanzi, Bradley T. Hyman, Deborah Blacker, Shibani S. Mukerji, M. Brandon Westover, Sudeshna Das
Dementia is a neurodegenerative disorder that causes cognitive decline and affects more than 50 million people worldwide. Dementia is under-diagnosed by healthcare professionals - only one in four people who suffer from dementia are diagnosed. Even when a diagnosis is made, it may not be entered as a structured International Classification of Diseases (ICD) diagnosis code in a patient's charts. Information relevant to cognitive impairment (CI) is often found within electronic health records (EHR), but manual review of clinician notes by experts is both time consuming and often prone to errors. Automated mining of these notes presents an opportunity to label patients with cognitive impairment in EHR data. We developed natural language processing (NLP) tools to identify patients with cognitive impairment and demonstrate that linguistic context enhances performance for the cognitive impairment classification task. We fine-tuned our attention based deep learning model, which can learn from complex language structures, and substantially improved accuracy (0.93) relative to a baseline NLP model (0.84). Further, we show that deep learning NLP can successfully identify dementia patients without dementia-related ICD codes or medications.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections