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Josephs, K.A., et al. (2013) Quantitative Neurofibrillary Tangle Density and Brain Volumetric MRI Analyses in Alzheimer’s Disease Presenting as Logopenic Progressive Aphasia. Brain and Language, 127, 127-134.
https://doi.org/10.1016/j.bandl.2013.02.003

has been cited by the following article:

• TITLE: The Future of Artificial Intelligence for Alzheimer’s Disease Diagnostics

  AUTHORS: Robert Logan, Sabrina S. Zerbey, Sean J. Miller

  KEYWORDS: Artificial Intelligence, Convolutional Neural Network, Disease Detection, Neu-rodegeneration, Alzheimer’s Disease

  JOURNAL NAME: Advances in Alzheimer's Disease, Vol.10 No.4, December 16, 2021

  ABSTRACT: Alzheimer’s disease (AD) is a leading cause of death, yet there is no disease-modifying drug therapy currently available. It is critical to establish a diagnosis of AD before clinical system onset so that drug therapies can start earlier. Unfortunately, this is not the current standard practice. Artificial intelligence (AI) holds tremendous promise for identifying AD related structural changes in brain scan images. This paper discusses the recent applications and potential future directions for AI in AD diagnostics. Annual brain scanning and computer vision-assisted early diagnosis is encouraged, so that disease-modifying drug therapy could begin earlier in the progressive pathology.