A whole-process interpretable and multi-modal deep reinforcement learning for diagnosis and analysis of Alzheimer’s disease ∗
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A whole-process interpretable and multi-modal deep reinforcement learning for diagnosis and analysis of Alzheimer’s disease
∗
Authors
Keywords
-
Journal
Journal of Neural Engineering
Volume 18, Issue 6, Pages 066032
Publisher
IOP Publishing
Online
2021-11-10
DOI
10.1088/1741-2552/ac37cc
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A simple nomogram prediction model to identify relatively young patients with mild cognitive impairment who may progress to Alzheimer’s disease
- (2021) Wenhong Chen et al. JOURNAL OF CLINICAL NEUROSCIENCE
- Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
- (2021) Guang Yang et al. Information Fusion
- Development and validation of an interpretable deep learning framework for Alzheimer’s disease classification
- (2020) Shangran Qiu et al. BRAIN
- Disease-associated astrocytes in Alzheimer’s disease and aging
- (2020) Naomi Habib et al. NATURE NEUROSCIENCE
- Simultaneous left atrium anatomy and scar segmentations via deep learning in multiview information with attention
- (2020) Guang Yang et al. Future Generation Computer Systems-The International Journal of eScience
- Greater effect of polygenic risk score for Alzheimer's disease among younger cases who are apolipoprotein E-ε4 carriers
- (2020) Brian Fulton-Howard et al. NEUROBIOLOGY OF AGING
- Associations between tau, Aβ, and cortical thickness with cognition in Alzheimer disease
- (2019) Rik Ossenkoppele et al. NEUROLOGY
- Sex Differences in the Association of Global Amyloid and Regional Tau Deposition Measured By Positron Emission Tomography in Clinically Normal Older Adults
- (2019) Rachel F. Buckley et al. JAMA Neurology
- Deep learning for Electroencephalogram (EEG) classification tasks: A review
- (2019) Alexander Craik et al. Journal of Neural Engineering
- ApoE4: an emerging therapeutic target for Alzheimer’s disease
- (2019) Mirna Safieh et al. BMC Medicine
- Predicting diagnosis and cognition with 18F-AV-1451 tau PET and structural MRI in Alzheimer's disease
- (2019) Niklas Mattsson et al. Alzheimers & Dementia
- In defense of the black box
- (2019) Elizabeth A. Holm SCIENCE
- Deep learning-based electroencephalography analysis: a systematic review
- (2019) Yannick Roy et al. Journal of Neural Engineering
- Quantitative Comparison of Conventional and t-SNE-guided Gating Analyses
- (2019) Shadi Toghi Eshghi et al. Frontiers in Immunology
- Deep learning and medical diagnosis
- (2019) Yuliang Liu et al. LANCET
- Understanding the impact of sex and gender in Alzheimer's disease: A call to action
- (2018) Rebecca A. Nebel et al. Alzheimers & Dementia
- DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction
- (2018) Guang Yang et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- APOE and Alzheimer’s Disease: Evidence Mounts that Targeting APOE4 may Combat Alzheimer’s Pathogenesis
- (2018) Md. Sahab Uddin et al. MOLECULAR NEUROBIOLOGY
- Inter-subject transfer learning with end-to-end deep convolutional neural network for EEG-based BCI
- (2018) Fatemeh Fahimi et al. Journal of Neural Engineering
- Tissue-type mapping of gliomas
- (2018) Felix Raschke et al. NeuroImage-Clinical
- Application of t-SNE to human genetic data
- (2017) Wentian Li et al. Journal of Bioinformatics and Computational Biology
- Age, APOE and sex: Triad of risk of Alzheimer’s disease
- (2016) Brandalyn C. Riedel et al. JOURNAL OF STEROID BIOCHEMISTRY AND MOLECULAR BIOLOGY
- Alzheimer's disease
- (2016) Philip Scheltens et al. LANCET
- Can we open the black box of AI?
- (2016) Davide Castelvecchi NATURE
- Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults
- (2015) Paula T. Trzepacz et al. BMC Geriatrics
- Sex modifies theAPOE-related risk of developing Alzheimer disease
- (2014) Andre Altmann et al. ANNALS OF NEUROLOGY
- ApoE and Aβ in Alzheimer’s Disease: Accidental Encounters or Partners?
- (2014) Takahisa Kanekiyo et al. NEURON
- Clinical epidemiology of Alzheimer’s disease: assessing sex and gender differences
- (2014) Michelle Mielke et al. Clinical Epidemiology
- An algorithmic approach to structural imaging in dementia
- (2013) L. Harper et al. JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
- Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers
- (2013) Clifford R Jack et al. LANCET NEUROLOGY
- Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study
- (2013) Victor L Villemagne et al. LANCET NEUROLOGY
- Sleep and Alzheimer disease pathology—a bidirectional relationship
- (2013) Yo-El S. Ju et al. Nature Reviews Neurology
- Accuracy of the Clinical Diagnosis of Alzheimer Disease at National Institute on Aging Alzheimer Disease Centers, 2005–2010
- (2012) Thomas G. Beach et al. JOURNAL OF NEUROPATHOLOGY AND EXPERIMENTAL NEUROLOGY
- Neuroimaging correlates of pathologically defined subtypes of Alzheimer's disease: a case-control study
- (2012) Jennifer L Whitwell et al. LANCET NEUROLOGY
- Apolipoprotein E in Alzheimer's disease and other neurological disorders
- (2011) Philip B Verghese et al. LANCET NEUROLOGY
- Addressing population aging and Alzheimer's disease through the Australian Imaging Biomarkers and Lifestyle study: Collaboration with the Alzheimer's Disease Neuroimaging Initiative
- (2010) Kathryn A. Ellis et al. Alzheimers & Dementia
- The clinical use of structural MRI in Alzheimer disease
- (2010) Giovanni B. Frisoni et al. Nature Reviews Neurology
- Age, Alzheimer disease, and brain structure
- (2009) C. A. Raji et al. NEUROLOGY
- Alzheimer's Disease Neuroimaging Initiative (ADNI): Clinical characterization
- (2009) R. C. Petersen et al. NEUROLOGY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started