034 Graph Algorithms and Visualization for Clinical Care Support of Pneumonia – NODES2022
We will take a deep dive into patient journeys through the Medical Information Mart for Intensive Care (MIMIC)-IV de-identified Electronic Medical Records (EMR) data from 2008-2019, for patients diagnosed with pneumonia.
Using Neo4j and GraphXR to effectively model and analyze clinical and physiological patient data at scale, we can enable researchers and clinical practitioners to:
* Visualize the patient journey across time
* Use graph algorithms for patient phenotyping and characterization
* Develop diagnoses and treatment recommendations based on cohort-level trends
* Advance AI-enabled patient outcome prediction
Join us for this talk to learn how to:
* Inject EMR data into a Neo4j graph database, connecting patient medical history, diagnoses, medications and procedures
* Use Neo4j Graph Data Science graph embedding algorithms to learn low-dimensional patient history representations
* Apply graph clustering algorithms to cluster patients into similar cohorts
* Use graph embeddings as input for identifying patients at high risk for 30-day readmission
* Use GraphXR to design a dashboard visualization for clinical use that allows clinicians to toggle between:
– A single patient view of their medical history
– A birds-eye view of the care path for similar patients
– An explainable AI view of the main factors informing a patient’s risk for 30-day readmission
Speakers: Ana Areias, Mengjia Kang
Format: Full Session 30-45 min
Level: Advanced
Topics: #graphdatascience , #visualization , #machinelearning , #healthcare , #advanced
Region: AMERICAS
Visit https://neo4j.com/video/nodes-2022/ learn more at https://neo4j.com/developer/get-started and engage at https://community.neo4j.com