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The Natural History of Alzheimer's Disease: Description of Study Cohort and Accuracy of Diagnosis
Abstract
OBJECTIVE: We describe the sampling, initial evaluation, and final diagnostic classification of subjects enrolled in a natural history study of Alzheimer's disease (AD). DESIGN: Volunteer cohort study. SETTING: Multidisciplinary behavioral neurology research clinic. PATIENTS OR OTHER PARTICIPANTS: Three-hundred nineteen individuals were enrolled in the Alzheimer Research Program between March 1983 and March 1988. Of these, 204 were originally classified with AD, 102 were normal elderly control subjects, and 13 were considered special cases. MAIN OUTCOME MEASURES: Final consensus clinical diagnosis, final neuropathologic diagnosis, and death. RESULTS: Of the 204 patients enrolled in the study, re-review after as many as 5 years of follow-up resulted in a final clinical classification of 188 with probable AD. Seven patients were believed to have a significant vascular component to the dementia, three were found to have developed depression, and six were excluded on other clinical grounds. Neuropathologic examination of 50 brains indicated definite AD in 43. After removing these seven misdiagnosed patients, the final group of probable/definite AD totaled 181 individuals. Accuracy of the baseline clinical diagnosis relative to neuropathology was 86%, and when follow-up clinical data were considered, 91.4%. Detailed neuropsychological testing yielded high sensitivity (0.988) and specificity (0.983) to dementia. Analyses of survival time from study entry until death revealed that older patients were significantly more likely to die during follow-up, but neither sex, years of education, nor pattern of cognitive impairment were related to survival. CONCLUSIONS: These data provide the descriptive basis for future studies of this cohort. They indicate that longitudinal follow-up of demented cases increases accuracy of diagnosis, and that detailed cognitive testing aids in early classification.
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Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
VALIDITY OF THE TRAIL MAKING TEST AS AN INDICATOR OF ORGANIC BRAIN DAMAGE
Reitan, R. M. (1958) · Perceptual and Motor Skills · doi:10.2466/pms.1958.8.3.271 · Cited by 8,167
Blessed, G., Tomlinson, B. E., & Roth, M. (1968) · British Journal of Psychiatry · doi:10.1192/bjp.114.512.797 · Cited by 4,117
The assessment of aphasia and related disorders
Goodglass, H., & Kaplan, E. (1972) · Medical Entomology and Zoology · Cited by 3,258
. Cerebral blood flow in dementia.
Hachinski, V. C., Iliff, L. D., Zilhka, E., Du Boulay, G. H., McAllister, V. L., Marshall, J., Russell, R. W. R., & Symon, L. (1975) · Archives of Neurology · doi:10.1001/archneur.1975.00490510088009 · Cited by 3,186
A Standardized Memory Scale for Clinical Use
Wechsler, D. (1945) · The Journal of Psychology · doi:10.1080/00223980.1945.9917223 · Cited by 2,949
BMPD statistical software manual
Dixon, W. (1988) · University of California Press eBooks · Cited by 2,536
Diagnosis of Alzheimer's Disease
Khachaturian, Z. S. (1985) · Archives of Neurology · doi:10.1001/archneur.1985.04060100083029 · Cited by 2,499
Le test de copie d'une figure complexe
Osterrieth, P. M. (1944) · Medical Entomology and Zoology · Cited by 2,336
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Fraser, K. C., Meltzer, J. A., & Rudzicz, F. (2015) · Journal of Alzheimer's Disease · doi:10.3233/jad-150520 · Cited by 797
FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer's disease
Foster, N. L., Heidebrink, J. L., Clark, C. M., Jagust, W. J., Arnold, S. E., Barbas, N. R., DeCarli, C. S., Scott Turner, R., Koeppe, R. A., Higdon, R., et al. (2007) · Brain · doi:10.1093/brain/awm177 · Cited by 608
A Review of Machine Learning and Deep Learning Approaches on Mental Health Diagnosis
Iyortsuun, N. K., Kim, S.-H., Jhon, M., Yang, H.-J., & Pant, S. (2023) · Healthcare · doi:10.3390/healthcare11030285 · Cited by 337
Lopez, O. L., Becker, J. T., Wahed, A. S., Saxton, J., Sweet, R. A., Wolk, D. A., Klunk, W., & DeKosky, S. T. (2009) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.2008.158964 · Cited by 266
Self-citationGarcía, S. D. L. F., Ritchie, C. W., & Luz, S. F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.06047 · Cited by 265
Deep learning for depression recognition with audiovisual cues: A review
He, L., Niu, M., Tiwari, P., Marttinen, P., Su, R., Jiang, J., Guo, C., Wang, H., Ding, S., Wang, Z., et al. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.10.012 · Cited by 273
Haider, F., García, S. D. L. F., & Luz, S. F. (2019) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2019.2955022 · Cited by 204
Holthoff, V. A., Beuthien-Baumann, B., Kalbe, E., Lüdecke, S., Lenz, O., Zündorf, G., Spirling, S., Schierz, K., Winiecki, P., Sorbi, S., et al. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.11.035 · Cited by 190
Research evaluation and diagnosis of possible Alzheimer’s disease over the last two decades: II
López, O. L., Becker, J. T., Klunk, W. E., Saxton, J. A., Hamilton, R. L., Kaufer, D., Sweet, R. A., MELTZER, C. C., Wisniewski, S. R., Kamboh, M. I., et al. (2000) · Neurology · doi:10.1212/wnl.55.12.1863 · Cited by 188
Self-citationLópez, O. L., Wisniewski, S. R., Becker, J. T., Boller, F., & DeKosky, S. T. (1999) · Archives of Neurology · doi:10.1001/archneur.56.10.1266 · Cited by 183
Self-citationGait Disturbance in Alzheimer's Disease: A Clinical Study
O’Keeffe, S. T., Kazeem, H. M., Philpott, R. M., Playfer, J. R., Gosney, M., & Lye, M. (1996) · Age and Ageing · doi:10.1093/ageing/25.4.313 · Cited by 168
Dopamine Receptor Genetic Variation, Psychosis, and Aggression in Alzheimer Disease
Sweet, R. A., Nimgaonkar, V. L., Kamboh, M. I., López, O. L., Zhang, F., & DeKosky, S. T. (1998) · Archives of Neurology · doi:10.1001/archneur.55.10.1335 · Cited by 164
Natural history of behavioural changes and psychiatric symptoms in Alzheimer's disease
Hope, T., Keene, J., Fairburn, C. G., Jacoby, R. J., & McShane, R. H. (1999) · The British Journal of Psychiatry · doi:10.1192/bjp.174.1.39 · Cited by 155
Artificial Intelligence for Alzheimer’s Disease: Promise or Challenge?
Fabrizio, C., Termine, A., Caltagirone, C., & Sancesario, G. M. (2021) · Diagnostics · doi:10.3390/diagnostics11081473 · Cited by 163
Frisoni, G. B., Govoni, S., Geroldi, C., Bianchetti, A., Calabresi, L., Franceschini, G., & Trabucchi, M. (1995) · Annals of Neurology · doi:10.1002/ana.410370509 · Cited by 149
Predicting dementia from spontaneous speech using large language models
Agbavor, F., & Liang, H. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000168 · Cited by 147
Predictors of mortality in patients with Alzheimer's disease living in nursing homes
Gambassi, G., Landi, F., Lapane, K. L., Sgadari, A., Mor, V., & Bernabei, R. (1999) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.67.1.59 · Cited by 136
Incorrect Diagnosis of Alzheimer's Disease: A Clinicopathologic Study
Klatka, L. A. (1996) · Archives of Neurology · doi:10.1001/archneur.1996.00550010045015 · Cited by 136
Roshanzamir, A., Aghajan, H. K., & Baghshah, M. S. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01456-3 · Cited by 140
Phonological and Articulatory Impairment in Alzheimer's Disease: A Case Series
Croot, K., Hodges, J. R., Xuereb, J. H., & Patterson, K. E. (2000) · Brain and Language · doi:10.1006/brln.2000.2357 · Cited by 133
Fallacies in the pathological confirmation of the diagnosis of Alzheimer's disease
Bowler, J. V., Muñoz, D. G., Merskey, H., & Hachinski, V. (1998) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.64.1.18 · Cited by 132
Balagopalan, A., Eyre, B., Rudzicz, F., & Novikova, J. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2557 · Cited by 166
Impairment of Neocortical Metabolism Predicts Progression in Alzheimer’s Disease
Herholz, K., Nordberg, A. K., Salmon, É., Perani, D., Kessler, J., Mielke, R., Halber, M., Jelić, V., Almkvist, O., Collette, F., et al. (1999) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000017196 · Cited by 131
Clinical Features of Alzheimer Disease With and Without Lewy Bodies
Chung, E. J., Babulal, G. M., Monsell, S. E., Cairns, N. J., Roe, C. M., & Morris, J. C. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2015.0606 · Cited by 130
Extrapyramidal Signs in Patients With Probable Alzheimer Disease
López, O. L., Wisnieski, S. R., Becker, J. T., Boiler, F., & DeKosky, S. T. (1997) · Archives of Neurology · doi:10.1001/archneur.1997.00550200033007 · Cited by 124
Self-citationThe Natural History of Alzheimer's Disease: A Brain Bank Study
Jost, B. C., & Grossberg, G. T. (1995) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.1995.tb07401.x · Cited by 123
Differential diagnosis of Alzheimer's disease
Geldmacher, D. S., & Whitehouse, P. J. (1997) · Neurology · doi:10.1212/wnl.48.5_suppl_6.2s · Cited by 122
Hernández-Domínguez, L., Ratté, S., Sierra, G., & Roche-Bergua, A. (2018) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2018.02.004 · Cited by 124
Describing the Cookie Theft picture
Cummings, L. (2019) · Pragmatics and Society · doi:10.1075/ps.17011.cum · Cited by 112
CERAD test performances in amnestic mild cognitive impairment and Alzheimer's disease
Karrasch, M., Sinervä, E., Gronholm, P. C., Rinne, J. O., & Laine, M. (2005) · Acta Neurologica Scandinavica · doi:10.1111/j.1600-0404.2005.00380.x · Cited by 111
López, O. L., Becker, J. T., Jungreis, C. A., Rezek, D. L., Estol, C. J., Boiler, F., & DeKosky, S. T. (1995) · Archives of Neurology · doi:10.1001/archneur.1995.00540310029012 · Cited by 109
Self-citationLavretsky, H., Siddarth, P., Kepe, V., Ercoli, L. M., Miller, K. J., Burggren, A. C., Bookheimer, S. Y., Huang, S., Barrio, J. R., & Small, G. W. (2009) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e3181953b82 · Cited by 108
DementiaBank: Theoretical Rationale, Protocol, and Illustrative Analyses
Lanzi, A. M., Saylor, A. K., Fromm, D., Liu, H., MacWhinney, B., & Cohen, M. L. (2023) · American Journal of Speech-Language Pathology · doi:10.1044/2022_ajslp-22-00281 · Cited by 117
Deep learning-based speech analysis for Alzheimer’s disease detection: a literature review
Yang, Q., Li, X., Ding, X., Xu, F., & Ling, Z.-H. (2022) · Alzheimer s Research & Therapy · doi:10.1186/s13195-022-01131-3 · Cited by 122
Neuropathologic Correlates of Late-Onset Major Depression
Sweet, R. A., Hamilton, R. L., Butters, M. A., Mulsant, B. H., Pollock, B. G., Lewis, D. A., López, O. L., DeKosky, S. T., & Reynolds, C. F. (2004) · Neuropsychopharmacology · doi:10.1038/sj.npp.1300554 · Cited by 105
Editorial: Alzheimer's Dementia Recognition through Spontaneous Speech
Luz, S., Haider, F., de la Fuente Garcia, S., Fromm, D., & MacWhinney, B. (2021) · Frontiers in Computer Science · doi:10.3389/fcomp.2021.780169 · Cited by 104
Classifying Alzheimer's Disease Using Audio and Text-Based Representations of Speech
Haulcy, R., & Glass, J. R. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.624137 · Cited by 110
Dementia Detection from Speech Using Machine Learning and Deep Learning Architectures
Kumar, M. R., Vekkot, S., Lalitha, S., Gupta, D., Govindraj, V. J., Shaukat, K., Alotaibi, Y. A., & Zakariah, M. (2022) · Sensors · doi:10.3390/s22239311 · Cited by 101
Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech
Balagopalan, A., Eyre, B., Robin, J., Rudzicz, F., & Novikova, J. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.635945 · Cited by 106
Non-cognitive symptoms in mild cognitive impairment subjects
López, O. L., Becker, J. T., & Sweet, R. A. (2005) · Neurocase · doi:10.1080/13554790490896893 · Cited by 98
Self-citationBoada, M., Anaya, F., Ortiz, P., Olazarán, J., Shua-Haim, J. R., Obisesan, T. O., Hernández, I., Muñoz, J., Buendia, M., Alegret, M., et al. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-160565 · Cited by 94
SpeechFormer++: A Hierarchical Efficient Framework for Paralinguistic Speech Processing
Chen, W., Xing, X., Xu, X., Pang, J., & Du, L. (2023) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2023.3235194 · Cited by 101
Mild cognitive impairment: Conceptual issues and structural and functional brain correlates
Saykin, A. J., & Wishart, H. A. (2003) · Seminars in Clinical Neuropsychiatry · doi:10.1053/scnp.2003.50002 · Cited by 93
Yeung, A., Iaboni, A., Rochon, E. A., Lavoie, M., Santiago, C., Yancheva, M., Novikova, J., Xu, M., Robin, J., Kaufman, L. D., et al. (2021) · Alzheimer s Research & Therapy · doi:10.1186/s13195-021-00848-x · Cited by 90
Mahajan, P., & Baths, V. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.623607 · Cited by 89
The Diagnosis of Alzheimer's Disease
Villareal, D. T., & Morris, J. C. (1999) · Journal of Alzheimer s Disease · doi:10.3233/jad-1999-14-506 · Cited by 87
Pennisi, G., Ferri, R., Lanza, G., Cantone, M., Pennisi, M., Puglisi, V., Malaguarnera, G., & Bella, R. (2011) · Journal of Neural Transmission · doi:10.1007/s00702-010-0554-9 · Cited by 85
Speech- and language-based classification of Alzheimer's disease: a systematic review
Vigo, I., Coelho, L., & Reis, S. (2022) · Bioengineering · doi:10.3390/bioengineering9010027 · Cited by 83
Speech based detection of Alzheimer's disease: a survey of AI techniques, datasets and challenges
Ding, K., Chetty, M., Noori Hoshyar, A., Bhattacharya, T., & Klein, B. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10961-6 · Cited by 82
Ford, E. M., Milne, R., & Curlewis, K. (2023) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1492 · Cited by 81
Comparative Evolution of Alzheimer Disease, Vascular Dementia, and Mixed Dementia
Bowler, J. V., Eliasziw, M., Steenhuis, R., Munoz, D. G., Fry, R., Merskey, H., & Hachinski, V. C. (1997) · Archives of Neurology · doi:10.1001/archneur.1997.00550180021007 · Cited by 75
Multimodal Inductive Transfer Learning for Detection of Alzheimer’s Dementia and its Severity
Sarawgi, U., Zulfikar, W. D., Soliman, N., & Maes, P. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-3137 · Cited by 89
Vliet, E. C.-V., Manly, J. J., Tang, M., Marder, K. S., Bell, K. L., & Stern, Y. (2003) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617703950053 · Cited by 77
Psychotic Symptoms in Alzheimer Disease: Evidence for Subtypes
Cook, S. E., Miyahara, S., Bacanu, S., Perez-Madriñan, G., López, O. L., Kaufer, D., Nimgaonkar, V. L., Wisniewski, S. R., DeKosky, S. T., & Sweet, R. A. (2003) · American Journal of Geriatric Psychiatry · doi:10.1097/00019442-200307000-00003 · Cited by 72
Predictors of progression in patients with AD and Lewy bodies
López, O. L., Wisniewski, S. R., Hamilton, R. L., Becker, J. T., Kaufer, D., & DeKosky, S. T. (2000) · Neurology · doi:10.1212/wnl.54.9.1774 · Cited by 71
Self-citationA Cross-modal Review of Indicators for Depression Detection Systems
Morales, M. R., Scherer, S. J., & Levitan, R. (2017) · Workshop on Computational Linguistics and Clinical Psychology (CLPsych) · doi:10.18653/v1/w17-3101 · Cited by 72
Zhang, J., Wu, J., Qiu, Y., Song, A., Li, W., Li, X., & Liu, Y. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.106517 · Cited by 69
Severity of cognitive impairment and the clinical diagnosis of AD with Lewy bodies
López, O. L., Hamilton, R. L., Becker, J. T., Wisniewski, S. R., Kaufer, D., & DeKosky, S. T. (2000) · Neurology · doi:10.1212/wnl.54.9.1780 · Cited by 69
Self-citationClarke, N., Foltz, P. W., & Garrard, P. (2020) · Cortex · doi:10.1016/j.cortex.2020.05.001 · Cited by 70
Alcohol, Dementia, and Alzheimer's Disease: Comparison of Neuropsychological Profiles
Saxton, J. A., Munro, C. A., Butters, M. A., Schramke, C. J., & McNeil, M. (2000) · Journal of Geriatric Psychiatry and Neurology · doi:10.1177/089198870001300308 · Cited by 68
Automatic Diagnosis of Alzheimer’s Disease Using Neural Network Language Models
Fritsch, J., Wankerl, S., & Nöth, E. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682690 · Cited by 68
Reported practices of primary care physicians in the diagnosis and management of dementia
Cody, M., Beck, C., Shue, V. M., & Pope, S. K. (2002) · Aging & Mental Health · doi:10.1080/13607860120101158 · Cited by 67
An automatic Alzheimer’s disease classifier based on spontaneous spoken English
Bertini, F., Allevi, D., Lutero, G., Calzà, L., & Montesi, D. (2022) · Computer Speech & Language · doi:10.1016/j.csl.2021.101298 · Cited by 66
Clinical symptoms in Alzheimer's disease
López, O. L., & DeKosky, S. T. (2008) · Handbook of clinical neurology · doi:10.1016/s0072-9752(07)01219-5 · Cited by 70
Liu, N., Luo, K., Yuan, Z., & Chen, Y. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.772592 · Cited by 66
The Framingham Brain Donation Program: Neuropathology Along the Cognitive Continuum
Au, R., Seshadri, S., Knox, K., Beiser, A., J. Himali, J., J. Cabral, H., Auerbach, S., C. Green, R., A. Wolf, P., & C. McKee, A. (2012) · Current Alzheimer Research · doi:10.2174/156720512801322609 · Cited by 65
Detecting Signs of Dementia Using Word Vector Representations
Mirheidari, B., Blackburn, D. J., Walker, T., Venneri, A., Reuber, M., & Christensen, H. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1764 · Cited by 59
Explainable Identification of Dementia From Transcripts Using Transformer Networks
Ilias, L., & Askounis, D. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3172479 · Cited by 70
Semantic Feature Extraction Using SBERT for Dementia Detection
Santander-Cruz, Y., Salazar-Colores, S., Paredes-García, W. J., Guendulain-Arenas, H., & Tovar‐Arriaga, S. (2022) · Brain Sciences · doi:10.3390/brainsci12020270 · Cited by 73
Perez-Madriñan, G., Cook, S. E., Saxton, J. A., Miyahara, S., López, O. L., Kaufer, D., Aizenstein, H. J., DeKosky, S. T., & Sweet, R. A. (2004) · American Journal of Geriatric Psychiatry · doi:10.1097/00019442-200409000-00003 · Cited by 65
Lindsay, H., Tröger, J., & König, A. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.642033 · Cited by 64
Speech Recognition in Alzheimer’s Disease and in its Assessment
Zhou, L., Fraser, K. C., & Rudzicz, F. (2016) · Interspeech 2016 · doi:10.21437/interspeech.2016-1228 · Cited by 62
Bryś, M., Glodzik, L., Mosconi, L., Switalski, R., Santi, S. D., Pirraglia, E., Rich, K. E., Kim, B. C., Mehta, P. D., Zinkowski, R., et al. (2009) · Journal of Alzheimer s Disease · doi:10.3233/jad-2009-0968 · Cited by 61
Chien, Y.-W., Hong, S.-Y., Cheah, W.-T., Yao, L.-H., Chang, Y., & Fu, L. (2019) · Scientific Reports · doi:10.1038/s41598-019-56020-x · Cited by 61
Weamer, E. A., Emanuel, J. E., Varón, D., Miyahara, S., Wilkosz, P. A., López, O. L., DeKosky, S. T., & Sweet, R. A. (2008) · International Psychogeriatrics · doi:10.1017/s1041610208007734 · Cited by 60
Neuroprotective Effects of Salidroside in a Mouse Model of Alzheimer’s Disease
Wang, H., Li, Q., Sun, S., & Chen, S. (2020) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-020-00801-w · Cited by 58
Exploring Deep Transfer Learning Techniques for Alzheimer's Dementia Detection
Zhu, Y., Liang, X., Batsis, J. A., & Roth, R. M. (2021) · Frontiers in Computer Science · doi:10.3389/fcomp.2021.624683 · Cited by 61
Rhetorical structure and Alzheimer’s disease
Abdalla, M., Rudzicz, F., & Hirst, G. (2017) · Aphasiology · doi:10.1080/02687038.2017.1355439 · Cited by 56
Learning Language and Acoustic Models for Identifying Alzheimer’s Dementia From Speech
Shah, Z., Sawalha, J., Tasnim, M., Qi, S.-A., Stroulia, E., & Greiner, R. (2021) · Frontiers in Computer Science · doi:10.3389/fcomp.2021.624659 · Cited by 56
Evolution of the diagnostic criteria for degenerative and cognitive disorders
López, O. L., McDade, E., Riverol, M., & Becker, J. T. (2011) · Current Opinion in Neurology · doi:10.1097/wco.0b013e32834cd45b · Cited by 58
Self-citationMartinc, M., Haider, F., Pollak, S., & Luz, S. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.642647 · Cited by 55
Zimmerer, V. C., Newman, L., Thomson, R., Coleman, M., & Varley, R. A. (2018) · Aphasiology · doi:10.1080/02687038.2018.1497138 · Cited by 54
WavBERT: Exploiting Semantic and Non-semantic Speech using Wav2vec and BERT for Dementia Detection
Zhu, Y., Obyat, A., Liang, X.-H., Batsis, J., & Roth, R. (2021) · Interspeech · doi:10.21437/interspeech.2021-332 · Cited by 80
Changing Patient Characteristics and Survival Experience in an Alzheimer’s Center Patient Cohort
Doody, R. S., Pavlik, V., Massman, P. J., Kenan, M., Yeh, S., Powell, S. Z.-E., Cooke, N., Dyer, C. B., Demirovic, J., Waring, S. C., et al. (2005) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000087300 · Cited by 56
Plasma Thiamine Deficiency Associated with Alzheimer's Disease but Not Parkinson's Disease
Gold, M., Hauser, R. A., & Chen, M. F. (1998) · Metabolic Brain Disease · doi:10.1023/a:1020678912330 · Cited by 55
Wilkosz, P. A., Miyahara, S., López, O. L., DeKosky, S. T., & Sweet, R. A. (2006) · American Journal of Geriatric Psychiatry · doi:10.1097/01.jgp.0000192500.25940.1b · Cited by 55
An N-Gram Based Approach to the Automatic Diagnosis of Alzheimer’s Disease from Spoken Language
Wankerl, S., Nöth, E., & Evert, S. (2017) · Interspeech (USB) · doi:10.21437/interspeech.2017-1572 · Cited by 52
Martinc, M., & Pollak, S. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2202 · Cited by 52
Orimaye, S. O., Wong, J. S.-M., & Wong, C. P. (2018) · PLOS ONE · doi:10.1371/journal.pone.0205636 · Cited by 52
Predicting 10‐Year Care Requirements for Older People with Suspected Alzheimer's Disease
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Metadata
- Authors
- Becker, J. T.
- Affiliations
- University of Pittsburgh Medical Center (US)
- Corresponding author
- Becker, James T.
- ORCID
- Becker, James T.
- Venue
- Archives of Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 1994-06-01
- Volume
- 51
- Issue
- 6
- Pages
- 585
- ISSN
- 0003-9942 (ISSN-L)
- OpenAlex
- W2074037951
- Cited by
- 576
- References
- 49
- Citations by year
- 2026: 53 · 2025: 67 · 2024: 63 · 2023: 59 · 2022: 53 · 2021: 61 · 2020: 62 · 2019: 26 · 2018: 15 · 2017: 14 · 2016: 7 · 2015: 7 · 2014: 1 · 2013: 1 · 2012: 2
- FWCI
- 5.79
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Archives of Neurology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5p01ag003705-04)
- National Institute on Aging (AG 05-133, P50AG005133, AG 03705)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neurological Disease Mechanisms and Treatments
- Keywords
- Alzheimer's disease, natural history (disease), diagnosis, neuropathologic diagnosis, diagnostic accuracy, dementia, neuropsychological assessment, survival, death, vascular dementia, depression, cohort studies
- MeSH terms
- Aged, Alzheimer Disease, Mental Disorders, Female, Humans, Male, Middle Aged, Nervous System, Nervous System Diseases, Neuropsychological Tests, Cohort Studies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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