Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data
出版年份 2019 全文链接
标题
Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data
作者
关键词
-
出版物
Frontiers in Aging Neuroscience
Volume 11, Issue -, Pages -
出版商
Frontiers Media SA
发表日期
2019-08-20
DOI
10.3389/fnagi.2019.00220
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- 2018 Alzheimer's disease facts and figures
- (2018) Alzheimers & Dementia
- Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging
- (2018) Hongyoon Choi et al. BEHAVIOURAL BRAIN RESEARCH
- Landmark-based deep multi-instance learning for brain disease diagnosis
- (2018) Mingxia Liu et al. MEDICAL IMAGE ANALYSIS
- Artificial intelligence faces reproducibility crisis
- (2018) Matthew Hutson SCIENCE
- Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images
- (2018) Donghuan Lu et al. Scientific Reports
- Mechanisms of Risk Reduction in the Clinical Practice of Alzheimer’s Disease Prevention
- (2018) Matthew W. Schelke et al. Frontiers in Aging Neuroscience
- Classification of Alzheimer’s Disease by Combination of Convolutional and Recurrent Neural Networks Using FDG-PET Images
- (2018) Manhua Liu et al. Frontiers in Neuroinformatics
- Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data
- (2018) Jorge Samper-González et al. NEUROIMAGE
- Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative
- (2018) Dallas P. Veitch et al. Alzheimers & Dementia
- Uncovering Biologically Coherent Peripheral Signatures of Health and Risk for Alzheimer’s Disease in the Aging Brain
- (2018) Brandalyn C. Riedel et al. Frontiers in Aging Neuroscience
- Prevention of Alzheimer's Disease: Lessons Learned and Applied
- (2017) James E. Galvin JOURNAL OF THE AMERICAN GERIATRICS SOCIETY
- A survey on deep learning in medical image analysis
- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
- (2017) Saima Rathore et al. NEUROIMAGE
- Global Data Sharing in Alzheimer Disease Research
- (2016) Naveen Ashish et al. ALZHEIMER DISEASE & ASSOCIATED DISORDERS
- The Cellular Phase of Alzheimer’s Disease
- (2016) Bart De Strooper et al. CELL
- Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
- (2016) Varun Gulshan et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease
- (2015) Siqi Liu et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- ImageNet Large Scale Visual Recognition Challenge
- (2015) Olga Russakovsky et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- A Robust Deep Model for Improved Classification of AD/MCI Patients
- (2015) Feng Li et al. IEEE Journal of Biomedical and Health Informatics
- Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
- (2014) Heung-Il Suk et al. NEUROIMAGE
- Deep learning for neuroimaging: a validation study
- (2014) Sergey M. Plis et al. Frontiers in Neuroscience
- Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
- (2013) David Moher ANNALS OF INTERNAL MEDICINE
- Latent feature representation with stacked auto-encoder for AD/MCI diagnosis
- (2013) Heung-Il Suk et al. Brain Structure & Function
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
- Learning Hierarchical Features for Scene Labeling
- (2012) Clement Farabet et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Chapter 11: Genome-Wide Association Studies
- (2012) William S. Bush et al. PLoS Computational Biology
- Validation in Genetic Association Studies
- (2011) I. R. Konig BRIEFINGS IN BIOINFORMATICS
- Pitfalls of supervised feature selection
- (2009) Pawel Smialowski et al. BIOINFORMATICS
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started