Lmst

Graphblas algorithms is a collection of GraphBLAS algorithms written using python-graphblas. It can be used directly or as a backend for NetworkX. It's fast, very fast.
#GraphAnalytics
https://github.com/python-graphblas/graphblas-algorithms

Graph analytics delight: emotion regulation as a transdiagnostic link between ADHD and depression symptoms.
https://capmh.biomedcentral.com/articles/10.1186/s13034-025-00966-6
#Graphs #GraphAnalytics

𝐇𝐨𝐰 𝐆𝐫𝐚𝐩𝐡 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐢𝐬 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐄𝐇𝐑 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐟𝐨𝐫 𝐏𝐫𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐌𝐞𝐝𝐢𝐜𝐢𝐧𝐞

Precision medicine relies on understanding individual variability in genetics and environment. Graph analytics offers a unique way to map these factors within Electronic Health Records (EHRs), helping care providers predict how different patients will respond to treatments.

#PrecisionMedicine #GraphAnalytics #EHR #PersonalizedCare #HealthcareInnovation

Second in the session was Wang & Wang's "Link Membership Inference Attacks against Unsupervised Graph Representation Learning," which investigates privacy vulnerabilities in UGRL models. (https://www.acsac.org/2023/program/final/s57.html) 3/4
#UnsupervisedLearning #PrivacyInAI #GraphAnalytics

Exploring a hierarchical #graph-based model for #mobilitydata representation and analysis

Today's post is a first quick dive into #Neo4J (really just getting my toes wet). It's based on a publicly available Neo4J dump containing #mobility data, ship trajectories to be specific.

#MobilityDataScience #MovementDataAnalytics #GraphAnalytics

http://anitagraser.com/2023/11/05/exploring-a-hierarchical-graph-based-model-for-mobility-data-representation-and-analysis/

Dabbling in #neo4j today, exploring Maryam M. Elayam's hierarchical graph-based model for mobility data https://zenodo.org/records/6405212

#MovementDataAnalytics #MobilityDataScience #GraphDatabase #GraphAnalytics