Nicholas Christakis, Yale – 2019 Stanford Medicine Big Data | Precision Health

Nicholas Christakis, Yale – 2019 Stanford Medicine Big Data | Precision Health

Publication date: Jul 10, 2019

Researchers and leaders from academia, hospitals, government and industry gathered for two days at the 2019 Big Data in Precision Health conference at Stanford Medicine to spark collaborations, address challenges, and identify actionable steps for using large-scale data analysis and technology to improve human health.

Nicholas Christakis, MD, PhD, of Yale University spoke on a panel about social determinants of health.

For more information, visit https://bigdata.stanford.edu/

Concepts Keywords
Alcoholics Anonymous Real social network
Algorithm Kind network
Amazon Mechanical Turk Left network
Artificial Intelligence Virtue network
Autonomous Vehicles Flows idea network
Bee Map networks network
Bigdata Villages network
Bioterrorist Color dissimilar neighbors
Bird Degree network
Broadway Problem axis probability
Carbon Diabetes care
Care System Social location network
Case Yellow Social networks networks
Catalyst Academic disciplines
Centrality Articles
Cognition Systems
Collective Action Problems Network theory
Cooperative Community building
Diabetes Social systems
Epidemic Experiments
Externalities Spillover
Genie Social network
Gini Coefficient Public goods game
Graft Psychology
Graphite Computer network
Happiness Artificial intelligence
Hardness Testing algorithms
Honduras
Hybrid
Imagine
India
Interact
Invisibility
Kindness
Lancet
Maternal Health
Moroccan
Network Topology
Pharmaceutical Agent
PhD
Probability
Public Good
Public Policy
Racism
Randomized Controlled Trial
Real People
Red Color
Secular
Smart Guy
Social Network
Social Networks
Social System
Society
Solved Game
Stanford
Transitive
Uganda
Vaccination
Village
Vitamin
Wealth Inequality
Whip
Yale

Semantics

Type Source Name
gene UNIPROT LARGE1
gene UNIPROT PDC

Similar

Original Article

Leave a Comment

Your email address will not be published. Required fields are marked *