The following publications are possibly variants of this publication:
- Modeling and prediction of clinical symptom trajectories in Alzheimer's disease using longitudinal dataNikhil Bhagwat, Joseph D. Viviano, Aristotle N. Voineskos, M. Mallar Chakravarty, Alzheimer's Disease Neuroimaging Initiative. ploscb, 14(9), 2018. [doi]
- Building machine learning models without sharing patient data: A simulation-based analysis of distributed learning by ensemblingAnup Tuladhar, Sascha Gill, Zahinoor Ismail, Nils D. Forkert, Alzheimer's Disease Neuroimaging Initiative. jbi, 106:103424, 2020. [doi]
- Data-driven stochastic model for quantifying the interplay between amyloid-beta and calcium levels in Alzheimer's diseaseHina Shaheen, Roderick Melnik, Sundeep Singh, Alzheimer's Disease Neuroimaging Initiative. sadm, 17(2), April 2024. [doi]
- Deep recurrent model for individualized prediction of Alzheimer's disease progressionWonsik Jung, Eunji Jun, Heung-Il Suk, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 237:118143, 2021. [doi]