ADAM‐1: A Novel AI driven approach to Alzheimer's disease Research and Multi‐modal Data Analytics
ADAM-1 offers a robust and consistent platform for multi-modal data analysis in Alzheimer's research. The system's human-machine interaction through natural language queries enhances data interpretability, expanding and broadening researchers' insights in analyzing such complex datasets. Future versions of ADAM will include blood biomarkers and neuroimaging thus enabling more comprehensive and precise diagnostics, advancing the understanding of the complicated and dynamic underlying mechanisms of Alzheimer's disease progression.
Authors
- Roozbeh Sadeghian (ORCID: https://orcid.org/0000-0001-6418-9859)
- V. Bucci
- John P. Haran (ORCID: https://orcid.org/0000-0001-7311-1121)
- Maria Vaida (ORCID: https://orcid.org/0000-0002-7869-1900)
- Ouyang Guo
- Doyle V. Ward (ORCID: https://orcid.org/0000-0002-4952-824X)
- Ziyuan Huang
- Cheorun Jo
- Vishaldeep Kaur Sekhon
- Mark Newman
Institutions
- Johns Hopkins University (US)
- Harrisburg University of Science and Technology (US)
- University of Massachusetts Chan Medical School (US)
- DeVry University (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70855_100530
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00