Focus on Health


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The objective of this focus area is to help advance data sharing, acquisition, integration, analysis and resulting insights in the pursuit of improved public health and health outcomes. This includes:

1. Enabling data sharing, acquisition and integration to develop knowledge and insight in the pursuit of improved health outcomes, including alternative health data sources such as environmental factors, social media and mobile health

2. Supporting the development and deployment of advanced analytics, including causal discovery and reasoning, artificial intelligence, and machine learning in biomedicine

3. Enabling data science collaborations in the support of precision medicine, including advanced decision support leveraging data to deliver customized and personalized knowledge, insight and recommendations


Current Projects on Health

COVID Information Commons

COVID Resources Page

Connected Healthcare Cybersecurity Workshop Series

Large-Scale Observational Health Research

Submit your project here


Upcoming Health Events


Health Professional Opportunities


Health Career Opportunities


Health Resources

COVID Information Commons: Unlocking COVID-19 Insights with Data Science, developed with help from NEBD Hub student volunteer, Aryan Naik

IEEE DataPort COVID-19 Open-Source Datasets

Connected Healthcare Integrated Systems Design Workshop Results, IEEE and NEBDHub

NIH Office of Data Science Strategy Announces New Initiative to Improve Access to NIH-funded Data


Health Success Stories

Hongyu Zhao

A scalable computational pipeline to develop polygenic risk scores from biobank data

Guest post by Hongyu Zhao,  Yale School of Public Health, Yale University This Success Story is a report on the results of the Northeast Big Data Innovation Hub’s 2020 Seed Fund program. The goal of this project was to address the computational and implementation issues by developing a unified and user-friendly web platform for practicing […]

Ho-Joon Lee

A landscape of virus-host protein-protein interactions in SARS-CoV-2 infection in humans by machine learning

Guest post by Ho-Joon Lee, Ph.D., Yale School of Medicine This Success Story is a report on the results of the Northeast Big Data Innovation Hub’s 2020 Seed Fund program. COVID Information Commons Presentation: A landscape of virus-host protein-protein interactions in SARS-CoV-2 infection in humans by machine learning Our goal with this Seed Fund project […]

Cheng

Nonlinear Dynamics and Machine Learning for Accurate Detection of Early-stage Atrial Fibrillation

Guest post by Changqing Cheng, Ph.D., Binghamton University, State University of New York This Success Story is a report on the results of the Northeast Big Data Innovation Hub’s 2020 Seed Fund program. The overarching goal of this Seed Fund project was to develop an integrated platform to integrate nonlinear dynamics analysis and data science […]