Deep Learning for Alzheimer Diagnostics and Decision Support

Alzheimer’s Disease is the cause of 60-70% of cases of Dementia, costs associated to diagnosis, treatment and care of patients with it is estimated to be in the range of a hundred billion dollars in USA. This blog post have some recent papers related to using Deep Learning for diagnostics and decision support related to Alzheimer’s disease.

  1. Clinical decision support for Alzheimer’s disease based on deep learning and brain network
    – Authors: C Hu, R Ju, Y Shen, P Zhou, Q Li (2016)
  2. Classification of Alzheimer’s Disease using fMRI Data and Deep Learning Convolutional Neural Networks
    – Authors: S Sarraf, G Tofighi (2016)
  3. Non-Invasive Detection of Alzheimerâ s Disease-Multifractality of Emotional Speech
    – Authors: S Bhaduri, R Das, D Ghosh (2016)
  4. Alzheimer’s Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network
    – Authors: E Hosseini (2016)
  5. Application of machine learning on postural control kinematics for the Diagnosis of Alzheimer’s disease
    – Authors: L Costa, Mf Gago, D Yelshyna, J Ferreira, Hd Silva… (2016)
  6. Multi-modality stacked deep polynomial network based feature learning for Alzheimer’s disease diagnosis
    – Authors: X Zheng, J Shi, Y Li, X Liu, Q Zhang (2016)
  7. Predicting Alzheimer’s disease: a neuroimaging study with 3D convolutional neural networks
    – Authors: A Payan, G Montana (2015)
  8. Linguistic Features Identify Alzheimer’s Disease in Narrative Speech
    – Authors: Kc Fraser, Ja Meltzer, F Rudzicz (2015)
  9. Detection of Alzheimer’s disease using group lasso SVM-based region selection
    – Authors: Z Sun, Y Fan, Bpf Lelieveldt, M Van De Giessen (2015)
  10. Anatomically Constrained Weak Classifier Fusion for Early Detection of Alzheimer’s Disease
    – Authors: D Domenger, P Coupé (2014)

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