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[1] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[2] Sebastian Ruder,et al. An overview of gradient descent optimization algorithms , 2016, Vestnik komp'iuternykh i informatsionnykh tekhnologii.
[3] R. Killiany,et al. Use of structural magnetic resonance imaging to predict who will get Alzheimer's disease , 2000, Annals of neurology.
[4] Frank Rudzicz,et al. Vector-space topic models for detecting Alzheimer’s disease , 2016, ACL.
[5] Mihaela van der Schaar,et al. Demystifying Black-box Models with Symbolic Metamodels , 2019, NeurIPS.
[6] Sylvester Olubolu Orimaye,et al. Correction: Deep language space neural network for classifying mild cognitive impairment and Alzheimer-type dementia , 2018, PloS one.
[7] Nino Antulov-Fantulin,et al. Exploring Interpretable LSTM Neural Networks over Multi-Variable Data , 2019, ICML.
[8] Nan Hua,et al. Universal Sentence Encoder , 2018, ArXiv.
[9] H. Brodaty,et al. The GPCOG: A New Screening Test for Dementia Designed for General Practice , 2002, Journal of the American Geriatrics Society.
[10] Yoav Goldberg,et al. A Primer on Neural Network Models for Natural Language Processing , 2015, J. Artif. Intell. Res..
[11] L. Kurlowicz,et al. The Mini Mental State Examination (MMSE). , 1999, Director.
[12] B Schmand,et al. Early detection of Alzheimer's disease using the Cambridge Cognitive Examination (CAMCOG) , 2000, Psychological Medicine.
[13] Romola S. Bucks,et al. Analysis of spontaneous, conversational speech in dementia of Alzheimer type: Evaluation of an objective technique for analysing lexical performance , 2000 .
[14] Yuval Pinter,et al. Attention is not not Explanation , 2019, EMNLP.
[15] Byron C. Wallace,et al. Attention is not Explanation , 2019, NAACL.
[16] Malaz Boustani,et al. Alzheimer's Association recommendations for operationalizing the detection of cognitive impairment during the Medicare Annual Wellness Visit in a primary care setting , 2013, Alzheimer's & Dementia.
[17] Manaal Faruqui,et al. Attention Interpretability Across NLP Tasks , 2019, ArXiv.
[18] Quoc V. Le,et al. Distributed Representations of Sentences and Documents , 2014, ICML.
[19] Kathleen C. Fraser,et al. Linguistic Features Identify Alzheimer's Disease in Narrative Speech. , 2015, Journal of Alzheimer's disease : JAD.
[20] Colleen Richey,et al. Aided diagnosis of dementia type through computer-based analysis of spontaneous speech , 2014, CLPsych@ACL.
[21] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..
[22] Sylvester Olubolu Orimaye,et al. Deep language space neural network for classifying mild cognitive impairment and Alzheimer-type dementia , 2018, PloS one.
[23] Jakob Uszkoreit,et al. A Decomposable Attention Model for Natural Language Inference , 2016, EMNLP.
[24] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[25] Carlos Guestrin,et al. "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.
[26] J. Becker,et al. The natural history of Alzheimer's disease. Description of study cohort and accuracy of diagnosis. , 1994, Archives of neurology.
[27] Alun D. Preece,et al. Interpretability of deep learning models: A survey of results , 2017, 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).
[28] D. Riesner,et al. Detection of single amyloid β-protein aggregates in the cerebrospinal fluid of Alzheimer's patients by fluorescence correlation spectroscopy , 1998, Nature Medicine.
[29] Natalie Parde,et al. Enriching Neural Models with Targeted Features for Dementia Detection , 2019, ACL.
[30] Kanghan Oh,et al. Classification and Visualization of Alzheimer’s Disease using Volumetric Convolutional Neural Network and Transfer Learning , 2019, Scientific Reports.
[31] Mohit Bansal,et al. Detecting Linguistic Characteristics of Alzheimer’s Dementia by Interpreting Neural Models , 2018, NAACL.
[32] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[33] B. Croisile,et al. Comparative Study of Oral and Written Picture Description in Patients with Alzheimer's Disease , 1996, Brain and Language.
[34] Yoav Goldberg,et al. Understanding Convolutional Neural Networks for Text Classification , 2018, BlackboxNLP@EMNLP.
[35] Quanshi Zhang,et al. Interpretable Convolutional Neural Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[36] Uma Shanker Tiwary,et al. Using Psycholinguistic Features for the Classification of Comprehenders from Summary Speech Transcripts , 2017, IHCI.
[37] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[38] S. Borson,et al. The Mini‐Cog: a cognitive ‘vital signs’ measure for dementia screening in multi‐lingual elderly , 2000, International journal of geriatric psychiatry.
[39] Heidi Christensen,et al. Detecting Signs of Dementia Using Word Vector Representations , 2018, INTERSPEECH.
[40] Lalana Kagal,et al. Explaining Explanations: An Overview of Interpretability of Machine Learning , 2018, 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA).
[41] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[42] Avanti Shrikumar,et al. Learning Important Features Through Propagating Activation Differences , 2017, ICML.