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2110 Total Publications

Structural Degradation Modeling Framework for Sparse Datasets with an application on Alzheimer’s Disease
Chehade, A and Liu, K
2019; Journal EEE Transactions on Automation Science and Engineering; vol. 16; no. 1; pp. 192-205;
Deep learning-based classification of multi-categorical Alzheimer’s disease data
Cohen, DS, Carpenter, KA, Jarrell, JT and Huang, X
2019; Journal Current Neurobiol; vol. 10; no. 3; pp. 141-147;
Mid-sagittal plane detection for advanced physiological measurements in brain scans
Bertacchini, F, Rizzo, R, Bilotta, E, Pantano, P, Luca, A, Mazzuca, A, Lopez, A and Alzheimers Dis, N
2019; Journal Physiological Measurement; vol. 40; no. 11; pp. 14;
Computer aided Alzheimer's disease diagnosis by an unsupervised deep learning technology
Bi, X, Li, S, Xiao, B, Li, Y, Wang, G and Ma, X
2019; Journal Neurocomputing;
Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction
Brand, L, Nichols, K, Wang, H, Shen, L and Huang, H
2019; Journal IEEE Trans Med Imaging;
White matter in different regions evolves differently during progression to dementia
Dadar, M, Maranzano, J, Ducharme, S, Collins, DL, Weiner, MW, Aisen, P, Weiner, M, Petersen, R, Jack, CR, Jagust, W, Trojanowki, JQ, Toga, AW, Beckett, L, Green, RC, Saykin, AJ, Morris, J, Shaw, LM, Khachaturian, Z, Sorensen, G, Carrillo, M, Kuller, L, Raichle, M, Paul, S, Davies, P, Fillit, H, Hefti, F, Holtzman, D, Mesulam, MM, Potter, W, Snyder, P, Lilly, E, Logovinsky, V, Montine, T, Jimenez, G, Donohue, M, Gessert, D, Harless, K, Salazar, J, Cabrera, Y, Walter, S, Hergesheimer, L, Harvey, D, Bernstein, M, Fox, N, Thompson, P, Schuff, N, DeCarli, C, Borowski, B, Gunter, J, Senjem, M, Vemuri, P, Jones, D, Kantarci, K, Ward, C, Koeppe, RA, Foster, N, Reiman, EM, Chen, KW, Mathis, C, Landau, S, Morris, JC, Cairns, NJ, Franklin, E, Taylor-Reinwald, L, Lee, V, Korecka, M, Figurski, M, Crawford, K, Neu, S, Foroud, TM, Potkin, S, Shen, L, Faber, K, Kim, S, Nho, K, Thal, L, Thal, L, Buckholtz, N, Snyder, PJ, Albert, M, Frank, R, Hsiao, J, Quinn, J, Silbert, LC, Lind, B, Kaye, JA, Carter, R, Dolen, S, Schneider, LS, Pawluczyk, S, Becerra, M, Teodoro, L, Spann, BM, Brewer, J, Vanderswag, H, Fleisher, A, Ziolkowski, J, Heidebrink, JL, Lord, JL, Mason, SS, Albers, CS, Knopman, D, Johnson, K, Villanueva-Meyer, J, Pavlik, V, Pacini, N, Lamb, A, Kass, JS, Doody, RS, Shibley, V, Chowdhury, M, Rountree, S, Dang, MM, Stern, Y, Honig, LS, Bell, KL, Yeh, R, Ances, B, Winkfield, D, Carroll, M, Oliver, A, Creech, ML, Mintun, MA, Schneider, S, Marson, D, Geldmacher, D, Love, MN, Griffith, R, Clark, D, Brockington, J, Grossman, H, Mitsis, E, Shah, RC, Lamar, M, Samuels, P, Duara, R, Greig-Custo, MT, Rodriguez, R, Onyike, C, D'Agostino, D, Kielb, S, Witbracht, M, Sadowski, M, Sheikh, MO, Singleton-Garvin, J, Ulysse, A, Gaikwad, M, Doraiswamy, PM, Petrella, JR, James, O, Borges-Neto, S, Wong, TZ, Coleman, E, Karlawish, JH, Wolk, DA, Vaishnavi, S, Clark, CM, Arnold, SE, Smith, CD, Jicha, G, Hardy, P, El Khouli, R, Oates, E, Conrad, G, Lopez, OL, Oakley, M, Simpson, DM, Porsteinsson, AP, Martin, K, Kowalksi, N, Keltz, M, Goldstein, BS, Makino, KM, Ismail, MS, Brand, C, Thai, G, Pierce, A, Yanez, B, Sosa, E, Womack, K, Mathews, D, Quiceno, M, Levey, AI, Lah, JJ, Cellar, JS, Burns, JM, Swerdlow, RH, Brooks, WM, Woo, E, Silverman, DHS, Teng, E, Kremen, S, Apostolova, L, Tingus, K, Lu, PH, Bartzokis, G, Graff-Radford, NR, Parfitt, F, Poki-Walker, K, Farlow, MR, Hake, AM, Matthews, BR, Brosch, JR, Herring, S, van Dyck, CH, Carson, RE, Varma, P, Chertkow, H, Bergman, H, Hosein, C, Black, S, Stefanovic, B, Heyn, C, Hsiung, GYR, Mudge, B, Sossi, V, Feldman, H, Assaly, M, Finger, E, Pasternack, S, Pavlosky, W, Rachinsky, I, Drost, D, Kertesz, A, Bernick, C, Munic, D, Mesulam, MM, Rogalski, E, Lipowski, K, Weintraub, S, Bonakdarpour, B, Kerwin, D, Wu, CK, Johnson, N, Sadowsky, C, Villena, T, Turner, RS, Johnson, K, Reynolds, B, Sperling, RA, Johnson, KA, Marshall, GA, Yesavage, J, Taylor, JL, Chao, S, Lane, B, Rosen, A, Tinklenberg, J, Zamrini, E, Belden, CM, Sirrel, SA, Kowall, N, Killiany, R, Budson, AE, Norbash, A, Johnson, PL, Obisesan, TO, Oyonumo, NE, Allard, J, Ogunlana, O, Lerner, A, Ogrocki, P, Tatsuoka, C, Fatica, P, Fletcher, E, Maillard, P, Olichney, J, Carmichael, O, Kittur, S, Borrie, M, Lee, TY, Bartha, R, Johnson, S, Asthana, S, Carlsson, CM, Tariot, P, Burke, A, Hetelle, J, DeMarco, K, Trncic, N, Reeder, S, Bates, V, Capote, H, Rainka, M, Scharre, DW, Kataki, M, Tarawneh, R, Zimmerman, EA, Celmins, D, Hart, D, Pearlson, GD, Blank, K, Anderson, K, Flashman, LA, Seltzer, M, Hynes, ML, Santulli, RB, Sink, KM, Yang, M, Mintz, A, Ott, BR, Tremont, G, Daiello, LA, Bodge, C, Salloway, S, Malloy, P, Correia, S, Lee, A, Rosen, HJ, Miller, BL, Perry, D, Mintzer, J, Spicer, K, Bachman, D, Pasternak, S, Rogers, J, Pomara, N, Hernando, R, Sarrael, A, Miller, DD, Smith, KE, Koleva, H, Nam, KW, Shim, H, Schultz, SK, Relkin, N, Chiang, G, Lin, M, Ravdin, L, Smith, A, Leach, C, Raj, BA, Fargher, K, Neylan, T, Grafman, J, Friedl, K, Hayes, J, Finley, S, Householder, E, Fleischman, D, Arfanakis, K, Varon, D, Greig, MT, Goldstein, B, Martin, KS, Potkin, SG, Preda, A, Nguyen, D, Massoglia, D, Brawman-Mintzer, O, Martinez, W, Rosen, H, Behan, K, Marshall, G, Sabbagh, MN, Jacobson, SA, Wolday, S, Johnson, SC, Fruehling, JJ, Harding, S, Peskind, ER, Petrie, EC, Li, G, Yesavage, JA, Furst, AJ, Mackin, S, Raman, R, Drake, E, Donohue, M, Shaffer, E, Nelson, C, Bickford, D, Butters, M, Zmuda, M, Reyes, D, Faber, KM, Nudelman, KN, Au, YH, Scherer, K, Catalinotto, D, Stark, S, Ong, E, Fernandez, D and Alzheimers Dis Neuroimaging, I
2019; Journal Neurobiology of Aging; vol. 76; pp. 71-79;
Benchmarking functional connectome-based predictive models for resting-state fMRI
Dadi, K, Rahim, M, Abraham, A, Chyzhyk, D, Milham, M, Thirion, B, Varoquaux, G and Alzheimers Dis Neuroimaging, I
2019; Journal Neuroimage; vol. 192; pp. 115-134;
Braak neurofibrillary tangle staging prediction from in vivo MRI metrics
Dallaire-Théroux, C, Beheshti, I, Potvin, O, Dieumegarde, L, Saikali, S and Duchesne, S
2019; Journal Alzheimers Dement (Amst); vol. 11; pp. 599-609;
An interpretable machine learning model for diagnosis of Alzheimer's disease
Das, D., Ito, J., Kadowaki, T. and Tsuda, K.
2019; Journal PeerJ; vol. 7; pp. e6543;