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Krauss JK, Droste DW, Vach W, et al. Cerebrospinal fluid shunting in idiopathic normal-pressure hydrocephalus of the elderly: effect of periventricular and deep white matter lesions. Neurosurgery 1996; 39:292\u2013299; discussion 299\u2013300.","DOI":"10.1097\/00006123-199608000-00011"},{"key":"6","doi-asserted-by":"crossref","unstructured":"6. Kazui H, Miyajima M, Mori E, Ishikawa M; SINPHONI-2 Investigators. Lumboperitoneal shunt surgery for idiopathic normal pressure hydrocephalus (SINPHONI-2): an open-label randomised trial. Lancet Neurol 2015; 14:585\u2013594.","DOI":"10.1016\/S1474-4422(15)00046-0"},{"key":"7","doi-asserted-by":"crossref","unstructured":"7. Birks J. Cholinesterase inhibitors for Alzheimer\u2019s disease. Cochrane Database Syst Rev 2006:CD005593.","DOI":"10.1002\/14651858.CD005593"},{"key":"8","doi-asserted-by":"crossref","unstructured":"8. Scheltens P, Fox N, Barkhof F, De Carli C. 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Differentiating shunt-responsive normal pressure hydrocephalus from Alzheimer disease and normal aging: pilot study using automated MRI brain tissue segmentation. J Neurol 2014; 261:1994\u20132002.","DOI":"10.1007\/s00415-014-7454-0"},{"key":"12","doi-asserted-by":"crossref","unstructured":"12. Miskin N, Patel H, Franceschi AM, et al. Diagnosis of normal-pressure hydrocephalus: use of traditional measures in the era of volumetric MR imaging. Radiology 2017; 285:197\u2013205.","DOI":"10.1148\/radiol.2017161216"},{"key":"13","unstructured":"13. Suk HI, Shen D. Deep learning-based feature representation for AD\/MCI classification. Med Image Comput Comput Assist Interv 2013; 16:583\u2013590."},{"key":"14","doi-asserted-by":"crossref","unstructured":"14. Liu S, Liu S, Cai W, et al. Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer\u2019s disease. 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Guidelines for management of idiopathic normal pressure hydrocephalus: second edition. Neurol Med Chir (Tokyo) 2012; 52:775\u2013809.","DOI":"10.2176\/nmc.52.775"},{"key":"19","doi-asserted-by":"crossref","unstructured":"19. McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer\u2019s disease: recommendations from the National Institute on Aging-Alzheimer\u2019s Association workgroups on diagnostic guidelines for Alzheimer\u2019s disease. Alzheimers Dement 2011; 7:263\u2013269.","DOI":"10.1016\/j.jalz.2011.03.005"},{"key":"20","doi-asserted-by":"crossref","unstructured":"20. Hawass NE. Comparing the sensitivities and specificities of two diagnostic procedures performed on the same group of patients. Br J Radiol 1997; 70:360\u2013366.","DOI":"10.1259\/bjr.70.832.9166071"},{"key":"21","unstructured":"21. Rasmus A, Valpola H, Honkala M, Berglund M, Raiko T. 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