公开(公告)号：US20240331878A1

公开(公告)日：2024-10-03

申请号：US18193918

申请日：2023-03-31

Applicant: IQVIA Inc.

Inventor： Yong CAI ,  Yanping LIU ,  Ruoxin LI ,  Emily ZHAO ,  Yilian YUAN

IPC: G16H50/70 ,  G06N3/08

CPC classification number: G16H50/70 ,  G06N3/08

Abstract: A method includes receiving data and integrating the data into a computing system. The method also includes applying a machine learning system to identify patients from the integrated data to place in one or more communities that include consumer-related data and social determinants of health data. The method also includes combining path projection, aggregation, and embedding to establish one or more paths to connect the patients to the communities based on the consumer-related data and/or the social determinants of health data in the one or more communities. The method also includes training a machine learning system to identify a correct path among the one or more established paths to place the patients on to be connected to the one or more communities.

公开(公告)号：US20230197255A1

公开(公告)日：2023-06-22

申请号：US17557282

申请日：2021-12-21

Applicant: IQVIA Inc.

Inventor： Yong CAI ,  Yanping LIU ,  Ruoxin LI ,  Emily ZHAO ,  Yilian YUAN ,  William MCCLELLAN

IPC: G16H40/20 ,  G06N20/00

CPC classification number: G16H40/20 ,  G06N20/00 ,  G06Q50/01

Abstract: Methods and systems to identify collaborative communities of individuals from graphs of multiple types of relationships amongst the individuals, including to mine data related to multiple types of relationships amongst individuals, construct graphs to represent the respective types of relationships amongst individuals, and perform a multiplex graph convolutional network (MGCN) artificial intelligence machine learning (AIML) analysis across the multiple graphs to identify the collaborative communities. A mathematical representation of the graphs may be learned/tuned to optimize clustering of the individuals. Multiple parameters (inter-graph weights, consensus regularization function) may be jointly tuned based on a joint optimization function. The collaborative communities may be displayed such that relative positions of the individuals represent measures of influence exerted by the respective individuals within the respective collaborative communities.