Alzheimer’s Disease Neuroimaging Initiative

5586 Total Publications

Year	Title	Author	Journal
2015	A novel cortical thickness estimation method based on volumetric Laplace–Beltrami operator and heat kernel	Wang, G., Zhang, X., Su, Q., Shi, J., Caselli, R. J., & Wang, Y.	Journal Medical Image Analysis;
2015	Exploratory graphical models of functional and structural connectivity patterns for Alzheimer's Disease diagnosis	Ortiz A1, Munilla J1, Álvarez-Illán I1, Górriz JM2, Ramírez J2; Alzheimer's Disease Neuroimaging Initiative	Journal Front Comput Neurosci;
2015	Multi-stage Biomarker Models for Progression Estimation in Alzheimer's Disease	Schmidt-Richberg, A., Guerrero, R., Ledig, C., Molina-Abril, H., Frangi, A. F., Rueckert, D., & The Alzheimer’s Disease Neuroimaging Inititative.	Journal Inf Process Med Imaging;
2015	Fusing Heterogeneous Data for Alzheimer's Disease Classification	Pillai, P. S., & Leong, T.-Y.	Journal Studies in Health Technology and Informatics;
2015	Linking Genetics of Brain Changes to Alzheimer's Disease: Sparse Whole Genome Association Scan of Regional MRI Volumes in the ADNI and AddNeuroMed Cohorts	Khondoker, M., Newhouse, S., Westman, E., Muehlboeck, J.-S., Mecocci, P., Vellas, B., … Simmons, A.	Journal Journal of Alzheimer's Disease;
2015	A Multi-Marker Genetic Association Test Based on the Rasch Model Applied to Alzheimer’s Disease	Wang W, Mandel J, Bouaziz J, Commenges D, Nabirotchkine S, Chumakov I, Cohen D, Guedj M; Alzheimer’s Disease Neuroimaging Initiative.	Journal PLoS One;
2015	Comparison of nine tractography algorithms for detecting abnormal structural brain networks in Alzheimer’s disease	Zhan L, Zhou J, Wang Y, Jin Y, Jahanshad N, Prasad G, Nir TM, Leonardo CD, Ye J, Thompson PM, For The Alzheimer's Disease Neuroimaging Initiative.	Journal Frontiers in Aging Neuroscience;
2015	Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis	Suk, H.-I., Lee, S.-W., & Shen, D.	Journal Brain Structure and Function;
2015	An Integrated Bioinformatics Approach for Identifying Genetic Markers that Predict Cerebrospinal Fluid Biomarker p-tau181/A􏰀1-42 Ratio in ApoE4-Negative Mild Cognitive Impairment Patients	Sun, Y., Bresell, A., Rantalainen, M., Hoglund, K., Lebouvier, T., & Salter, H.	Journal Journal of Alzheimer's Disease;
2015	Functional Activities Questionnaire items that best discriminate and predict progression from clinically normal to mild cognitive impairment	Marshall GA, Zoller AS, Lorius N, Amariglio RE, Locascio JJ, Johnson KA, Sperling RA, Rentz DM, and for the Alzheimer’s Disease Neuroimaging Initiative.	Journal Current Alzheimer's Research;