The purpose of this proposal is to develop a combination of innovative statistical and data visualization approaches using patient-generated health data, including mobile health (mHealth) data from wearable devices and smartphones, and patient-reported outcomes, to improve outcomes for patients with Inflammatory Bowel Diseases (IBDs). This research will offer new insights into how to process and transform patient-generated health data into precise lifestyle recommendations to help achieve remission of symptoms.
The specific aims of this research are: 1) To develop new preprocessing methods for publicly available, heterogeneous, time-varied mHealth data to develop a high quality mHealth dataset; 2) To develop and apply novel machine learning methods to obtain accurate predictions and formal statistical inference for the influence of lifestyle features on disease activity in IBDs; and 3) To design and develop innovative, interactive data visualization tools for knowledge discovery. The methods developed in the areas of preprocessing of mHealth data, calibration for mHealth devices, machine learning, and interactive data visualization will be broadly applicable to other mHealth data, chronic conditions beyond IBDs, and other fields in which the data streams are highly variable, intermittent, and periodic. This work is highly relevant to the mission of the NIH BD2K initiative which supports the development of innovative and transformative approaches and tools to accelerate the integration of Big Data and data science into biomedical research. This project will also enhance training in the development and use of methods for biomedical Big Data science and mentor the next generation of multidisciplinary scientists.

Public Health Relevance

The proposed research is relevant to public health by seeking to improve symptoms for patients with inflammatory bowel diseases, which are chronic, life-long conditions with waxing and waning symptoms. Developing novel statistical and visualization methods to provide a more nuanced understanding of the precise relationship between physical activity and sleep to disease activity is relevant to BD2K's mission.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB025024-02
Application #
9572992
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lash, Tiffani Bailey
Project Start
2017-09-30
Project End
2020-06-30
Budget Start
2018-07-01
Budget End
2019-06-30
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599