Two datasets - Project Baseline and Alzheimer’s Disease Neuroimaging Initiative are affecting the way we look at healthcare. Data analysis is a key part of how we make decisions and changes in medicine; through digitization of this data, researchers are able to reduce costs and improve outcomes.
Project Baseline, a study created through the collaboration between Duke School of Medicine, Stanford, and Google, aims to take raw health data and create a baseline of this data that would be used to visualize connections between distinct populations. These connections can be utilized to make more informed decisions and to have a better understanding of health and disease. Participants are asked to take health tests, give bodily samples, and answer questionnaires about their health and lifestyles. Sensors and wearable devices are also provided to the participants to record heart rate, activity levels, and sleep habits.
Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a highly curated data set that contains MRI and PET images, genetics, cognitive tests, CSF, and blood biomarkers to help predict the onset of Alzheimer’s Disease. The purpose of gathering this data is to research new treatments that will slow and stop the progression of Alzheimer’s Disease. Researchers participating in the study follow a uniform procedure and protocol to ensure that any inconsistencies are eliminated. The data is free and available to any authorized researchers who request the data.
Gathering and maintaining data is necessary in research, but data-sharing is also important; validating results and furthering research from prior results all stem from promoting data-sharing. The National Science Foundation has started a project to supply resources and bring attention to data management principles called Sustainable Digital Data Preservation and Access Network Partners (DataNet).
Similar to the Visible Human Project, having highly curated datasets means that research can be reproducible, results can be verified, and across disciplines, researchers can make more connections when datasets are well maintained and shared.
