This is an in-progress research project at the interface of cognitive science and data science. Our aim is to create a web-based interactive tool for visualization, prediction, and classification of Alzheimer’s Disease, based on data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

What is ADNI?

quotes The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer’s disease patients, mild cognitive impairment subjects, and elderly controls. quotes

Figure1: Trajectory of five biomarkers from cognitive normal to AD.

Figure2: Detailed ADNI measures and data collection periods

Images are taken from the ADNI webpage


General Information:

image Please be aware that the analyses includes data from ADNI 1, ADNI 2,
ADNI 3, and ADNI Go.

Label keys:
  • AD = Alzheimer’s Disease
  • MCI = Mild Cognitive Impairment
  • CN = Cognitive Normal (Healthy Older Adults)
Time point keys:
  • bl = baseline
  • m12-m96 = 12 months - 96 months
Variables consists of:
  • Biomarkers:
    • Amyloid-Beta
    • Tau
    • P-Tau
    • APOE-4 (0, 1, or 2 allele)
  • Cognitive tests:
    • Mini-mental state examination (MMSE) higher is better
    • Montreal Cognitive Assessment(MoCA) higher is better
    • Clinical Demential Rating Scale lower is better
    • ADAS cognitve test 13 items lower is better
    • RAVLT Immediate score higher is better
    • Digit Span Score higher is better
  • Brain Volume:
    • Hippocampus
    • Entorhinal cortex
    • Middle Temporal
    • Ventricles
    • Intracranial Vault Volume


We are a group of graduate students at the University of Rochester who are part of the National Science Foundation Research Traineeship in Data Enabled Research into Human Behavior and its Cognitive and Neural Mechanisms. More information about this traineeship can be found at http://www.sas.rochester.edu/dsc/graduate/nrt.html

About the team


Greta Smith is a first-year data science MS candidate. Her research interests include data-driven advancement of healthcare and disease management. She received her bachelor’s degree in neuroscience from the University of Rochester in 2015.


Max Wasserman is a first year phd student in the Computer Science department. He completed a BSE in mechanical engineering at the University of Pennsylvania in 2015.


Ying Lin is a first-year Brain and Cognitive Sciences PhD student. She received her bachelor’s degree in behavioral neuroscience and Japanese from Colgate University in 2015.




1) Video explaintion of Alzheimer's Disease:                        2) Information about ADNI:

There are about 1,700 publications that used the ADNI dataset. Graph shown on left is by Yao et al.(2017), article titled: "Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer’s disease neuroimaging initiative"

Click Here for a list of publications.
Click Here for full article by Yao et al., 2017.

Association is one of the largest organizations that strives for Alzheimer's research, care, and support.
Click Here for more information.

All the interactive analysis are completed via R Shiny
Click Here for more information about Shiny.


We would like to thank:

Dr. Florian Jaeger for his guidance throughout the project.

Dr. Anton Porsteinsson for providing insightful and extensive background of ADNI.

Dr. Vankee Lin for her feedback during the earlier stage of our project.


image Ying Lin
Email: ylin78@ur.rochester.edu

Greta Smith
Email: gsmith21@ur.rochester.edu

Max Wasserman
Email: mwasser6@ur.rochester.edu